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  • Articles  (6,600)
  • International Journal of Distributed Sensor Networks  (2,573)
  • 163708
  • Electrical Engineering, Measurement and Control Technology  (6,600)
  • Energy, Environment Protection, Nuclear Power Engineering
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  • Articles  (6,600)
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  • Electrical Engineering, Measurement and Control Technology  (6,600)
  • Energy, Environment Protection, Nuclear Power Engineering
  • 1
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    Energy-efficient chain-based data gathering applied to communicating concrete (2020)
    Sage Publications
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    Publication Date: 2020-08-01
    Description: Wireless Sensor Networks are very convenient to monitor structures or even materials, as in McBIM project (Materials communicating with the Building Information Modeling). This project aims to develop the concept of “communicating concretes,” which are concrete elements embedding wireless sensor networks, for applications dedicated to Structure Health Monitoring in the construction industry. Due to applicative constraints, the topology of the wireless sensor network follows a chain-based structure. Node batteries cannot be replaced or easily recharged, it is crucial to evaluate the energy consumed by each node during the monitoring process. This area has been extensively studied leading to different energy models to evaluate energy consumption for chain-based structures. However, no simple, practical, and analytical network energy models have yet been proposed. Energy evaluation models of periodic data collection for chain-based structures are proposed. These models are compared and evaluated with an Arduino XBee–based platform. Experimental results show the mean prediction error of our models is 5%. Realizing aggregation at nodes significantly reduces energy consumption and avoids hot-spot problem with homogeneous consumptions along the chain. Models give an approximate lifetime of the wireless sensor network and communicating concretes services. They can also be used online by nodes for a self-assessment of their energy consumptions.
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  • 2
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    Experimental investigation of concrete strength curve based on pull-out post-insert method (2020)
    Sage Publications
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    Publication Date: 2020-07-01
    Description: As concrete is a building material that is widely used in the field of infrastructure construction, and its quality is related to the quality and service life in infrastructure engineering, concrete strength is an important reference index that reflects the concrete quality. Based on this, two commercial concretes A and B are selected in Henan Province, China, to perform the concrete strength test under same condition curing and standard condition curing in the pull-out post-insert method, cubic compression, rebound method, and drilling core method. The relationships between the different curing conditions, cubic compressive strength, core sample strength, rebound strength, and pull-out force of different commercial concretes are compared and analyzed. Through a comparative analysis and while considering the convenience and accuracy requirements, the strength curves of the two different concretes based on the pull-out post-insert method were fitted and analyzed, and the local strength curve test in Henan based on the pull-out post-insert method was established. The research results provide technical support for evaluating the strength of concrete structures using the pull-out post-insert method, which has important engineering significance for improving the popularize and application of the pull-out post-insert method.
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  • 3
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    Jointly designed quasi-cyclic LDPC-coded cooperation with diversity combining at receiver (2020)
    Sage Publications
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    Publication Date: 2020-07-01
    Description: This correspondence proposes a jointly-designed quasi-cyclic (QC) low-density parity-check (LDPC)-coded multi-relay cooperation with a destination node realized by multiple receive antennas. First, a deterministic approach is utilized to construct different classes of binary QC-LDPC codes with no length-4 cycles. Existing methods put some limitations in terms of code length and rate in order to provide high error-correction performance. Therefore, this article gives three classes of QC-LDPC codes based on a combinatoric design approach, known as cyclic difference packing (CDP), with flexibility in terms of code-length and rate selection. Second, the proposed CDP-based construction is utilized to jointly-design QC-LDPC codes for coded-relay cooperation. At the receiver, the destination node is realized by multiple receive antennas, where maximal-ratio combining (MRC) and sum-product algorithm (SPA)-based joint iterative decoding are utilized to decode the corrupted sequences coming from the source and relay nodes. Simulation results show that the proposed QC-LDPC coded-relay cooperations outperform their counterparts with a coding gain of about 0.25 dB at bit-error rate (BER) [Formula: see text] over a Rayleigh fading channel in the presence of additive white Gaussian noise. Furthermore, the extrinsic-information transfer (EXIT) chart analysis has been used to detect the convergence threshold of proposed jointly-designed QC-LDPC codes. Numerical analysis shows that the proposed jointly-designed QC-LDPC codes provide a better convergence as compared to their counterparts under the same conditions.
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  • 4
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    A hybrid dual-mode trust management scheme for vehicular networks (2020)
    Sage Publications
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    Publication Date: 2020-07-01
    Description: Vehicular ad-hoc networks allow vehicles to exchange messages pertaining to safety and road efficiency. Building trust between nodes can, therefore, protect vehicular ad-hoc networks from malicious nodes and eliminate fake messages. Although there are several trust models already exist, many schemes suffer from varied limitations. For example, many schemes rely on information provided by other peers or central authorities, for example, roadside units and reputation management centers to ensure message reliability and build nodes’ reputation. Also, none of the proposed schemes operate in different environments, for example, urban and rural. To overcome these limitations, we propose a novel trust management scheme for self-organized vehicular ad-hoc networks. The scheme is based on a crediting technique and does not rely on other peers or central authorities which distinguishes it as an economical solution. Moreover, it is hybrid, in the sense it is data-based and entity-based which makes it capable of revoking malicious nodes and discarding fake messages. Furthermore, it operates in a dual-mode (urban and rural). The simulation has been performed utilizing Veins, an open-source framework along with OMNeT++, a network simulator, and SUMO, a traffic simulator. The scheme has been tested with two trust models (urban and rural). The simulation results prove the performance and security efficacy of the proposed scheme.
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  • 5
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    Mobile target localization based on iterative tracing for underwater wireless sensor networks (2020)
    Sage Publications
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    Publication Date: 2020-07-01
    Description: In underwater wireless sensor networks, sensor position information has important value in network protocols and collaborative detection. However, many challenges were introduced in positioning sensor nodes due to the complexity of the underwater environment. Aiming at the problem of the stratification effect of underwater acoustic waves, the long propagation delay of messages, as well as the mobility of sensor nodes, a mobile target localization scheme for underwater wireless sensor network is proposed based on iterative tracing. Four modules are established in the mobile target localization based on iterative tracing: the data collection and rough position estimation, the estimation and compensation of propagation delay, the node localization, and the iteration. The deviation of distance estimation due to the assumption that acoustic waves propagate along straight lines in an underwater environment is compensated by the mobile target localization based on iterative tracing, and weighted least squares estimation method is used to perform linear regression. Moreover, an interacting multiple model algorithm is put forward to reduce the positioning error caused by the mobility of sensor nodes, and the two services of node time synchronization and localization assist each other during the iteration to improve the accuracy of both parties. The simulation results show that the proposed scheme can achieve higher localization accuracy than the similar schemes, and the positioning errors caused by the above three problems can be reduced effectively.
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  • 6
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    UAV Recharging Opportunities and Policies for Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: Recharging sensor networks using Unmanned Aerial Vehicles (UAVs) provides a possible method for increasing network lifetime. In this paper, we evaluate that approach, determining how much of a benefit it provides and under what conditions. We base our simulations and field experiments on data collected from charging with our UAV-based wireless power transfer system, which has similar transfer ranges and efficiencies as other such systems. We determine that a UAV can increase the network lifetime up to 290% compared to no recharging, that the UAV should recharge 30% of the sensor node battery capacity at one time for the maximum benefit, and that the UAV should recharge the lowest powered node until the network reaches a size of approximately 306 nodes at which point it should recharge the sink. We also examine how the sensor network can aid this through sink selection. The policy varies as network size increases, with a static approach working well until 200 nodes, and then either a perimeter or heuristic approach works best. These results inform future use of UAVs in recharging and working with sensor networks.
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  • 7
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    An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality.
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  • 8
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    Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time-consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with low overhead. In this paper, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.
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  • 9
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    A Grid-Based Linear Least Squares Self-Localization Algorithm in Wireless Sensor Network (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Self-localization is one of the key technologies in the wireless sensor networks (WSN). Some traditional self-localization algorithms can provide a reasonable positioning accuracy only in a uniform and dense network, while for a nonuniform network the performance is not acceptable. In this paper, we presented a novel grid-based linear least squares (LLS) self-localization algorithm. The proposed algorithm uses the grid method to screen the anchors based on the distribution characteristic of a nonuniform network. Furthermore, by taking into consideration the quasi-uniform distribution of anchors in the area, we select suitable anchors to assist the localization. Simulation results demonstrate that the proposed algorithm can greatly enhance the localization accuracy of the anonymous nodes and impose less computation burden compared to traditional Trilateration and Multilateration.
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  • 10
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    CTLL: A Cell-Based Transfer Learning Method for Localization in Large Scale Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Localization is emerging as a fundamental component in wireless sensor network and is widely used in the field of environmental monitoring, national and military defense, transportation monitoring, and so on. Current localization methods, however, focus on how to improve accuracy without considering the robustness. Thus, the error will increase rapidly when nodes density and SNR (signal to noise ratio) have changed dramatically. This paper introduces CTLL, Cell-Based Transfer Learning Method for Localization in WSNs, a new way for localization which is robust to the variances of nodes density and SNR. The method combines samples transfer learning and SVR (Support Vector Regression) regression model to get a better performance of localization. Unlike past work, which considers that the nodes density and SNR are invariable, our design applies regional division and transfer learning to adapt to the variances of nodes density and SNR. We evaluate the performance of our method both on simulation and realistic deployment. The results show that our method increases accuracy and provides high robustness under a low cost.
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  • 11
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    On Minimum-Latency Broadcast in Multichannel Duty-Cycled Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Broadcast has critical significance for wide application of wireless sensor networks (WSNs). Minimum-latency broadcast (MLB) studies how to devise a broadcast schedule, which can achieve minimum broadcast latency with no signal interference. In multichannel duty-cycled WSNs, nodes can exploit multiple channels to communicate and periodically fall asleep after working for some time. Nevertheless, most solutions to the MLB problem either focus on nonsleeping scenarios or only exploit one single channel. Therefore, we investigate the MLB problem in multichannel duty-cycled WSNs in this paper and call this problem as MLBCD problem. We prove that MLBCD problem is NP-hard. We propose a new concept of active interference graph (AIG). Based on AIG, we present one novel approximation broadcast algorithm called NAB to solve the MLBCD problem. We prove that our proposed NAB algorithm achieves provable performance guarantee. The results of our extensive evaluations show that NAB algorithm can significantly improve the broadcast latency.
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  • 12
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    A Group Mining Method for Big Data on Distributed Vehicle Trajectories in WAN (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: A distributed parallel clustering method MCR-ACA is proposed by integrating the ant colony algorithm with the computing framework Map-Combine-Reduce for mining groups with the same or similar features from big data on vehicle trajectories stored in Wide Area Network. The heaviest computing burden of clustering is conducted in parallel at local nodes, of which the results are merged to small size intermediates. The intermediates are sent to the central node and clusters are generated adaptively. The great overhead of transferring big volume data is avoided by MCR-ACA, which improves the computing efficiency and guarantees the correctness of clustering. MCR-ACA is compared with an existing parallel clustering algorithm on practical big data collected by the traffic monitoring system of Jiangsu province in China. Experimental results demonstrate that the proposed method is effective for group mining by clustering.
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  • 13
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    Kalman Filter-Based Indoor Position Tracking with Self-Calibration for RSS Variation Mitigation (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: This paper investigates the indoor position tracking problem under the variation of received signal strength (RSS) characteristic from the changes of device statuses and environmental factors. A novel indoor position tracking algorithm is introduced to provide reliable position estimates by integrating motion sensor-based positioning (i.e., dead-reckoning) and RSS-based fingerprinting positioning with Kalman filter. In the presence of the RSS variation, RSS-based fingerprinting positioning provides unreliable results due to different characteristics of RSS measurements in the offline and online phases, and the tracking performance is degraded. To mitigate the effect of the RSS variation, a recursive least square estimation-based self-calibration algorithm is proposed that estimates the RSS variation parameters and provides the mapping between the offline and online RSS measurements. By combining the Kalman filter-based tracking algorithm with the self-calibration, the proposed algorithm can achieve higher tracking accuracy even in severe RSS variation conditions. Through extensive computer simulations, we have shown that the proposed algorithm outperforms other position tracking algorithms without self-calibration.
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  • 14
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    A Self-Adaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: With the development of wireless communication and sensor techniques, source localization based on sensor network is getting more attention. However, fewer works investigate the multiple source localization for binary sensor network. In this paper, a self-adaptive particle swarm optimization based multiple source localization method is proposed. A detection model based on Neyman-Pearson criterion is introduced. Then the maximum likelihood estimator is employed to establish the objective function which is used to estimate the location of sources. Therefore, the multiple-source localization problem is transformed into optimization problem. In order to improve the ability of global search of particle swarm optimization, the self-adaptive particle swarm optimization is used to solve this problem. Various simulations have been conducted, and the results show that the proposed method owns higher localization accuracy in comparison with other methods.
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  • 15
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    Localization Algorithm in Wireless Sensor Networks Based on Multiobjective Particle Swarm Optimization (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Based on multiobjective particle swarm optimization, a localization algorithm named multiobjective particle swarm optimization localization algorithm (MOPSOLA) is proposed to solve the multiobjective optimization localization issues in wireless sensor networks. The multiobjective functions consist of the space distance constraint and the geometric topology constraint. The optimal solution is found by multiobjective particle swarm optimization algorithm. Dynamic method is adopted to maintain the archive in order to limit the size of archive, and the global optimum is obtained according to the proportion of selection. The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping a limited archive size by a method using the global optimal selection operator and dynamically maintaining the archive.
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  • 16
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    Lightweight Anomaly Detection for Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Anomaly detection in wireless sensor networks (WSNs) is critical to ensure the quality of senor data, secure monitoring, and reliable detection of interesting and critical events. The main challenge of anomaly detection algorithm in WSNs is identifying anomalies with high accuracy while consuming minimal resource of the network. In this paper two lightweight anomaly detection algorithms LADS and LADQA are proposed for WSNs. Both algorithms utilize the one-class quarter-sphere support vector machine (QSSVM) and convert the linear optimization problem of QSSVM to a sort problem for the reduced computational complexity. Experimental results show that the proposed algorithms can keep the lower computational complexity without reducing the accuracy for anomaly detection, compared to QSSVM.
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  • 17
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    Position Prediction Based Frequency Control of Beacons in Vehicular Ad Hoc Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: In VANETs, frequent beacon broadcasting can lead to high bandwidth consumption and channel congestion. In this paper, a position prediction based beacon approach is proposed to reduce beacon frequency and decrease bandwidth consumption. Vehicles track their neighbors using the predicted position instead of using periodic beacon broadcasting. Only when the prediction error is higher than a predefined tolerance will a beacon broadcasting be triggered. For improving the prediction accuracy, we classify the motion of vehicles into two typical patterns: a constant speed pattern and a maneuvering pattern. A maneuver detection module is responsible for recognizing current motion patterns, and a variable dimension filter that can switch dynamically between the two patterns is employed to generate high accurate position prediction. The simulation results show the proposed scheme can reduce significantly the number of beacons than three existing beacon approaches.
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  • 18
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    Energy Efficient Cooperative Sleep Control Using Small Cell for Wireless Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: The demand for higher throughput and more reliable quality of service (QoS) explosive increases the number of base stations in future wireless networks, which causes severe energy waste problems in wireless networks, especially when base stations are in low traffic load status. This paper has two main contributions: first of all, we propose a semistatic energy efficient method to find out the optimal on-off pattern considering the interference from adjacent base stations using integer convex optimization, from which the optimal on-off proportion of base stations could be obtained; then we propose a novel energy efficient cooperative heuristic algorithm in dynamic scenario, by separating the waiting time into two independent Markov processes using the new method; the total power consumption could be reduced significantly by adopting the novel method. Compared with reference method, simulation results indicate that in semistatic scenario, the total system power consumption could be reduced up to 26%, and, in dynamic scenario, the system power consumption could be reduced up to 40%.
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  • 19
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    Determining Sensor Locations in Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Network lifetime plays an important role in the design of wireless sensor networks. This paper studies the problem of prolonging the wireless sensor network’s lifetime, through introducing additional sensors at proper locations to achieve the goal of minimizing the length of the longest edge in the network. The problem is in fact the bottleneck Steiner tree problem, trying to find a Steiner tree minimizing the length of the longest edges for the given terminals in the Euclidean plane by introducing at most Steiner points. A restricted bottleneck Steiner tree problem is studied in this paper, which requires that only degree 3 Steiner points are not allowed to be adjacent in the optimal solution. We show that the restricted problem is MAX-SNP hard and cannot be approximated within performance ratio in polynomial time unless = NP; we first propose a polynomial time -approximation algorithm and then improve the ratio to for any given , by presenting a polynomial time randomized approximation algorithm, which is almost optimal to the restricted problem.
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  • 20
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    A Task Allocation Algorithm Based on Score Incentive Mechanism for Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: A wireless sensor network (WSN) consists of many resource constraint sensor nodes, which are always deployed in unattended environment. Therefore, the sensor nodes are vulnerable to failure and malicious attacks. The failed nodes have a heavily negative impact on WSNs’ real-time services. Therefore, we propose a task allocation algorithm based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes’ task execution in cluster-based WSNs, where cluster heads are responsible for task allocation and scores’ calculation. Based on the task scores, cluster members can collaborate with each other to complete complex tasks. In addition, the uncompleted tasks on failed nodes can be timely migrated to other cluster members for further execution. Furthermore, the uncompleted tasks on death nodes can be reallocated by cluster heads. Simulation results demonstrate that TASIM is quite suitable for real-time task allocation. In addition, the performance of the TASIM is clearly better than that of conventional task allocation algorithms in terms of both network load balance and energy consumption.
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  • 21
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    Network Coding for Severe Packet Reordering in Multihop Wireless Networks (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: Network coding is known to be effective in overcoming packet losses and packet reordering in multihop wireless networks. Despite the benefits, network coding is hard to deploy without being compatible with TCP. To address this problem, a seminal paper proposed a network coding scheme that adopts an ACK-based sliding-widow network coding approach. In this paper we show that the previous scheme may not suffice to mitigate the effects of packets received out of order in multipath wireless networks where severe packet reordering persists. We propose a modified network coding layer where the receiver acknowledges every degree of freedom by using the sequence number of a newly seen packet instead of using that of the oldest unseen packet so that the network coding layer can be compatible with a TCP variant for severe packet reordering. To reduce the decoding matrix size and the coding buffer size, our scheme allows retransmission at the network coding layer. Simulation results show that our scheme outperforms the exiting scheme in multipath wireless networks particularly when severe packet reordering persists.
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  • 22
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    Localization in an Industrial Environment: A Case Study on the Difficulties for Positioning in a Harsh Environment (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: While indoor localization has become a highly growing application domain in the last few years, it is hardly investigated in industrial environments. Interferences of magnetic fields, shadowing, and multipath propagation discourage positioning system vendors from porting their techniques to these harsh environments. However, the actual influence of these interferences on the positioning accuracy and the differences between an industrial and a nonindustrial environment have never been evaluated. This paper analyzes the actual differences for a positioning technique that is based on Wi-Fi fingerprinting, map matching, dead reckoning, filtering, and a plausibility determination. An investigation of the Wi-Fi signal strengths and compass sensor values in an industrial and a nonindustrial environment thereby showed that the differences between them are significant. In fact, it shows that more interferences and shadowing in the industrial environment resulted in even more accurate positioning.
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  • 23
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    Development of an Inexpensive Sensor Network for Recognition of Sitting Posture (2015)
    Hindawi
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    Publication Date: 2015-08-03
    Description: The aim of this work is the development of a network of wireless devices to determine, along with a time-stamp, postural changes of users that are to be used in personalized learning environments. For this purpose, we have designed a basic low-cost pressure sensor that can be built from components easily available. Several of these basic sensors (of sizes and shapes chosen specifically for the task) are integrated into a posture sensor cushion, which is electronically controlled by an Arduino microcontroller board. This accounts for experiments involving either a single cushion to be used by an individual end-user setting approach or classroom approaches where several of these cushions make up a sensor network via ZigBee wireless connections. The system thus formed is an excellent alternative to other more expensive commercial systems and provides a low-cost, easy-to-use, portable, scalable, autonomous, flexible solution with free hardware and software, which can be integrated with other sensing devices into a larger affect detection system, customizable to cope with postural changes at required time intervals and support single and collective oriented experimentation approaches.
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    Collaborative Routing Protocol Based on Hydrodynamics for Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Collaborative routing protocol design is hard work for wireless sensor networks (WSNs), especially for the large scale WSNs. The complexity and collaboration associated with the routing protocol design must be taken into account. A collaborative hydrodynamics routing (HR) protocol based on hydrodynamic theory is proposed in this paper, which aims at prolonging the network lifetime and adapting to the variety of network scales. Packets for forwarding in sensor networks can be analogous to fluid elements moving in a fluid field. Sink nodes are similar to the sink flows and source nodes are similar to the source flows; and packets would flow from sources to sinks under potential flow. Simulation results show that our approach has a great advantage as it offers a significant improvement in the aspects of decreasing complexity and prolonging network lifetime and demonstrates high performance for the improvement in collaboration of routing protocol. Comparing with conventional AODV protocol, HR achieves higher successful delivery rate and longer network lifetime by 50% and 40%, respectively.
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    An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Monitoring systems for the safety of building structure (SBS) can provide people with important data related to main supporting points in a building and then help people to make a reasonable maintenance schedule. However, more and more data bring a challenge for data management and data mining. In order to meet this challenge, under the framework of Wisdom Web of Things (W2T), we design a monitoring system for the SBS by using the semantic and the multisource data fusion technologies. This system establishes a dynamical data cycle among the physical world (buildings), the social world (humans), and the cyber world (computers) and provides various services in the monitoring process to alleviate engineers’ workload. Furthermore, all data in the cyber world are organized as the raw data, the semantic information, and the multisource knowledge. Based on this organization, we can concentrate on the data fusion from the viewpoints of time, space, and multisensor. At last, a prototype system powered by the semantic platform LarKC is tested from the aspects of sample performance and time consumption. In particular, noisy data (i.e., inconsistent, abnormal, or error data) are detected through the fusion of multisource knowledge, and some rule-based reasoning is conducted to provide personalized service.
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    Improved Route Discovery Based on Constructing Connected Dominating Set in MANET (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: A mobile ad hoc network (MANET) is widely applied in various urgent scenarios, benefiting from its feature that the hosts can communicate with each other without any physical infrastructure. An efficient routing function plays a critical role in MANET, and routing based on CDS is a promising approach. In this paper, a novel approach is proposed to obtain a stable routing path and prolong lifetime of MANET, by integrating three factors such as energy, mobility, and degree for the status of node minimum connected dominating set (SoN-MCDS). Extensive simulations show that the proposed protocol is superior to other classical ones in terms of lifetime and low energy consumption.
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    A Robust Home Alone Faint Detection Based on Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Target detection and tracking are one of the fundamental problems for wireless sensor networks and play an important role in the safety field. Faint detection is an important problem for the elderly people or patients or even pregnant women. It has wide application in current society. This paper proposed a method to collect information about the behavior and position of faint event in the sensing environment. This method detects and tracks faint person by combining Kalman filter and Camshift tracking algorithm. Experiments showed that the method yields good detection and tracking performance in complex environments.
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    Com-BIS: A Community-Based Barter Incentive Scheme in Socially Aware Networking (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Socially aware networking (SAN) provides a new paradigm for intermittently connected networks which exploits social properties of mobile users to guide the design of protocols. In SAN, data forwarding performance will be degraded dramatically due to the existence of users' selfish behaviors. To address the selfishness problem, barter-based incentive scheme is a fair approach in which two encounter nodes exchange the same amount of data with one another. However, it is a challenging issue for nodes to decide when two nodes contact and how many messages they will exchange for their next contacts. We consider this problem as a resource allocation problem and propose a community-based Barter incentive scheme for SAN paradigm (Com-BIS). In this method, network nodes are grouped into communities and they allocate their forwarding services for different communities optimally using 0-1 knapsack algorithm. The simulation results show that Com-BIS stimulates selfish nodes to cooperate in data delivery for other nodes effectively which improves the forwarding performance considerably.
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    Emergence in User Experience and Quality of Service for Internet of Things (2015)
    Hindawi
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    Publication Date: 2015-08-20
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    Mobile Localization Based on Received Signal Strength and Pearson’s Correlation Coefficient (2015)
    Hindawi
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    Publication Date: 2015-08-20
    Description: Being applicable for almost every scenario, mobile localization based on cellular network has gained increasing interest in recent years. Since received signal strength indication (RSSI) information is available in all mobile phones, RSSI-based techniques have become the preferred method for GSM localization. Although the GSM standard allows for a mobile phone to receive signal strength information from up to seven base stations (BSs), most of mobile phones only use the information of the associated cell as its estimated position. Therefore, the accuracy of GSM localization is seriously limited. In this paper, an algorithm for GSM localization is proposed with RSSI and Pearson’s correlation coefficient (PCC). The information of seven cells, including the serving cell and six neighboring cells, is used to accurately estimate the mobile location. With redundant information, the proposed algorithm restrains the error of Cell-ID and shows good robustness against environmental change. Without any additional device or prior statistical knowledge, the proposed algorithm is implementable on common mobile devices. Furthermore, in the practical test, its maximum error is below 550 m, which is 100 m better than that of Cell-ID, and the mean error is below 150 m, which is 250 m better than Cell-ID.
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    Cooperative Sensor Selection Optimization and Power-Efficient Gathering for Multihop Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Since a single sensor may be in a fading dip, cooperative sensing among multiple sensors which experience uncorrelated fading is required to guarantee reliable sensing performance. This paper proposes a cooperative sensor selection and power-efficient gathering (CSSPEG) strategy in multihop wireless sensor networks to avoid the “hot spot” problem. Intracluster communication radiuses have different sizes, in which the clusters closer to the base station have smaller size. Furthermore, intracluster member allocation scheme uses cooperative sensor selection and power-efficient gathering strategy. Simulation results show that the proposed CSSPEG can efficiently balance the energy consumption of cluster heads and prolong the lifetime of the network.
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    A Collaborative Data Gathering Mechanism Based on Fuzzy Decision for Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: In spite of the increasing demand for all kinds of sensing services and applications, there still lacks a clear understanding of collaborative techniques to design collaborative protocols for wireless sensor networks. This paper proposes collaborative data gathering mechanism based on fuzzy decision for wireless sensor networks. The proposed algorithm integrates some key parameters, for example, nodes’ residual energy level, the number of neighbors, centrality degree, and distance to the sink, into fuzzy decision. Numerical and simulation results validate the proposed algorithm for the networks in finding the optimum cluster heads and realizing better performances in clusters distribution and energy efficiency improvement.
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    Securing Body Sensor Networks with Biometric Methods: A New Key Negotiation Method and a Key Sampling Method for Linear Interpolation Encryption (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: We present two approaches that exploit biometric data to address security problems in the body sensor networks: a new key negotiation scheme based on the fuzzy extractor technology and an improved linear interpolation encryption method. The first approach designs two attack games to give the formal definition of fuzzy negotiation that forms a new key negotiation scheme based on fuzzy extractor technology. According to the definition, we further define a concrete structure of fuzzy negotiation that can enlarge the types of biometric data used to negotiate shared keys between biosensor nodes. The second approach includes a detailed key sampling method that uses shared secrets to generate linear interpolation factors and an improved linear interpolation encryption scheme based on linear equation group. Security analyses show that these two approaches are secure and can resist attacks launched by Ultra-Wide Band (UWB) technology, which has not received due attention in the existing studies.
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    A Self-Adaptive and Link-Aware Beaconless Forwarding Protocol for VANETs (2015)
    Hindawi
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    Publication Date: 2015-08-20
    Description: With the development of networks, Vehicular Ad-hoc Networks (VANETs) which act as the emerging application enhance the potential power of networks on the traffic safety and the entertainment. However, the high mobility and the dynamic nature of VANETs lead to the unreliable link which causes unreachable transmission and degrades the performance of the routing protocol in terms of the quality of experience (QoE). To provide a reliable routing for the data transmission, a self-adaptive and link-aware beaconless forwarding (SLBF) protocol is proposed. Based on the receiver based forwarding (RBF) scheme, SLBF designs a self-adaptive forwarding zone which is used to make the candidate nodes accurate. Furthermore, it proposes a comprehensive algorithm to calculate the waiting time by taking the greedy strategy, link quality, and the traffic load into account. With the NS-2 simulator, the performance of SLBF is demonstrated. The results show that the SLBF makes a great improvement in the delivery ratio, the end-to-end delay, and the average hops.
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    Implementation and Real-Time and Reliability Evaluation of a WHMS Improved by LHRP and SMAM (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: A dynamic heterogeneous and multihop (DHMH) wireless health monitoring system (WHMS) as a three-tier semi-self-organizing health monitoring network was presented. From bottom to top, the first tire of the network is the mobile data acquisition layer (DAL), the second tire of the network is the data transporting layer (DTL), and the third tire of the network is the data collection layer (DCL). A RF power control based topology management mechanism is proposed to balance the network load and to improve the network throughput. A lightweight hierarchical routing protocol (LHRP) was designed to reduce the transmission delay and improve the network throughput. For the mobile DAL nodes, the seamless mobile access mechanism (SMAM) was designed to ensure the low packet loss ratio. To evaluate the network performance, the end-to-end delay, the averaged reception ratio, and the network throughput of the DHMH were tested and the results proved that the network performance of the DHMH was improved.
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    An Adaptive Spanning Tree-Based Data Collection Scheme in Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: In-network data aggregation is a widely used method for collecting data efficiently in wireless sensor networks (WSNs). The authors focus on how to achieve high aggregation efficiency and prolonging networks’ lifetime. Firstly, this paper proposes an adaptive spanning tree algorithm (AST), which can adaptively build and adjust an aggregation spanning tree. Owing to the strategies of random waiting and alternative father nodes, AST can achieve a relatively balanced spanning tree and flexible tree adjustment. Then a redundant aggregation scheme (RAG) is illustrated. In RAG, interior nodes help to forward data for their sibling nodes and thus provide reliable data transmission for WSN. Finally, the simulations demonstrate that (1) AST can prolong the lifetime and (2) RAG makes a better trade-off between storage and aggregation ratio, comparing to other aggregation schemes.
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    An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Finding fastest driving routes is significant for the intelligent transportation system. While predicting the online traffic conditions of road segments entails a variety of challenges, it contributes much to travel time prediction accuracy. In this paper, we propose O-Sense, an innovative online-traffic-prediction based route finding mechanism, which organically utilizes large scale taxi GPS traces and environmental information. O-Sense firstly exploits a deep learning approach to process spatial and temporal taxi GPS traces shown in dynamic patterns. Meanwhile, we model the traffic flow state for a given road segment using a linear-chain conditional random field (CRF), a technique that well forecasts the temporal transformation if provided with further supplementary environmental resources. O-Sense then fuses previously obtained outputs with a dynamic weighted classifier and generates a better traffic condition vector for each road segment at different prediction time. Finally, we perform online route computing to find the fastest path connecting consecutive road segments in the route based on the vectors. Experimental results show that O-Sense can estimate the travel time for driving routes more accurately.
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    URALP: Unreachable Region Aware Location Privacy against Maximum Movement Boundary Attack (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: As location-based services have become popular, thereby exposed user locations raised serious privacy concerns. A typical measure for location privacy is to report blurred locations and ensure that other users coexist in the reported region. However, additional knowledge about the user’s maximum speed and the territorial information in user’s vicinity can allow for the adversary to effectively compromise the user’s location privacy. In this paper, we present an anonymization algorithm that effectively counters such attacks while achieving k-anonymity requirements as well as minimum acceptable cloaked region size. We evaluate our anonymization scheme using state-of-the-art simulators for both vehicular movements and pedestrian movements. The experimental results demonstrate the effectiveness and efficiency of our proposed algorithm.
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    Adaptive Localization in Wireless Sensor Network through Bayesian Compressive Sensing (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: The estimation of the localization of targets in wireless sensor network is addressed within the Bayesian compressive sensing (BCS) framework. BCS can estimate not only target locations but also noise variance of the environment. Furthermore, we provide adaptive iteration BCS localization (AIBCSL) algorithm, which is based on BCS and will choose measurement sensors according to the environment adaptively with only an initial value, while other frameworks require prior knowledge such as target numbers to choose measurements. AIBCSL suppose that environment noise variance is identical in interested area in a short period of time and change measurement numbers until terminal condition is reached. To suppress noise, we optimize estimation result by energy threshold strategy (ETS), which takes that transmit energy of noise focused on single grid is much lower than signal into consideration. And multisnapshot BCS (MT-BCS) will be explained and lead to a good result in low SNR level situation.
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    A Privacy-Preserving Continuous Location Monitoring System for Location-Based Services (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: To protect users’ private locations in location-based services, various location anonymization techniques have been proposed. The most commonly used technique is spatial cloaking, which organizes users’ exact locations into cloaked regions (CRs). This satisfies the K-anonymity requirement; that is, the querier is not distinguishable among K users within the CR. However, the practicality of cloaking techniques is limited due to the lack of privacy-preserving query processing capacity, for example, providing answers to the user’s spatial queries based on knowledge of the user’s cloaked location rather than the exact location. This paper proposes a cloaking system model called anonymity of motion vectors (AMV) that provides anonymity for spatial queries. The proposed AMV minimizes the CR of a mobile user using motion vectors. In addition, the AMV creates a ranged search area that includes the nearest neighbor (NN) objects to the querier who issued a CR-based query. The effectiveness of the proposed AMV is demonstrated in simulated experiments.
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    Cooperative Spectrum Sensing in Cognitive Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Cognitive wireless sensor network (CWSN) is a combination of cognitive radio and wireless sensor networks (WSNs), which can effectively solve spectrum resource scarcity problem in WSNs. As one of the key technologies in CWSNs, spectrum sensing enables sensors to detect and opportunistic access underutilized idle licensed bands, which remarkably improves the spectrum utilization and system performance. And cooperative spectrum sensing (CSS) has emerged to enhance detection performance of spectrum sensing. Focusing on CSS schemes in CWSNs, this paper explores the cooperative and noncooperative schemes comprehensively. The characteristics of the existing CSS schemes are analyzed in CWSNs. And then, according to the behavior of cognitive sensors, CSS techniques are classified into noncooperative and cooperative schemes. Concentrating on energy consumption, cooperative CSS schemes are classified into three categories: censoring, clustering, and sensor selection. The performance of three kinds of CSS schemes is compared and analyzed thoroughly. Finally, the difficulties and challenges of CSS scheme are addressed in CWSNs.
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    Probabilistic Trust Evaluation with Inaccurate Reputation Reports (2015)
    Hindawi
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    Publication Date: 2015-06-04
    Description: We are concerned with the problem of trust evaluation in the generic context of large scale open-ended systems. In such systems the truster agents have to interact with other trustee peers to achieve their goals, while the trustees may not behave as required in practice. The truster therefore has to predict the behaviors of potential trustees to identify reliable ones, based on past interaction experience. Due to the size of the system, often there is little or no past interaction between the truster and the trustee, that is, the case wherein the truster should resort to the third party agents, termed advisors here, inquiring about the reputation of the trustee. The problem is complicated by the possibility that the advisors may deliberately provide inaccurate and even misleading reputation reports to the truster. To this end, we develop techniques to take account of inaccurate reputations in modeling the behaviors of the trustee based on the Bayesian formalism. The core of the techniques is a proposed notion, termed Advisor-to-Truster relevance measure, based on which the incorrect reputation reports are rectified for use in the trust evaluation process. The benefit induced by the proposed techniques is verified by simulated experiments.
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    An Event-Driven Object Localization Method Assisted by Beacon Mobility and Directional Antennas (2015)
    Hindawi
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    Publication Date: 2015-06-05
    Description: An event-driven object localization method based on directional antennas is proposed in this paper. First the event occurrence spot is divided into four sections. Then low altitude UAV (Unmanned Aerial Vehicle) is employed to deploy DAWSN (Wireless Sensor Networks for Disaster Assistance) for urgent observation and communication. By means of a mobile anchor with four directional antennas and a GPS module, obstacle avoidance traverse in DAWSN is realized and the locations during mobility are broadcast. Unknown nodes take these locations as virtual anchors and project them onto a virtual motion path, and then the coordinates of unknown nodes are solved with extended directional localization method. This range-free method does not require plenty of anchor nodes and complicated computation. With small positioning error and large positionable node ratio (PNR), it allows the virtual anchor to move along any curve path and can be utilized under the event-driven scenario to provide self-localization for DAWSN.
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    Distributed Wireless Measurement System for Transient Pressure with Data Extraction Technology (2015)
    Hindawi
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    Publication Date: 2015-06-09
    Description: Transient pressure measurement system applied in an explosion field is usually characterized by non-real-time measurement due to the conflict between quick signal acquisition and limited communication bandwidth. The correct signal acquisition is launched by triggering, but the false triggering often leads to measurement failure due to the fact that the operating status of system cannot be real-time detected in an explosion condition. A distributed wireless measurement system with data extraction technology is proposed in this paper to improve the reliability of transient pressure measurement. A long-time signal acquisition is achieved by mass data storage to eliminate the trigger mode. On the other hand, an effective data segment is extracted by signal identification, which improves the efficiency of data transmission and data processing. A measurement system based on data extraction technology was designed and implemented in an explosion field, and the measurement node was characterized by sampling rate of 1 Msps, data storage of 128 Gb, effective data segment of 512 kW, and Wi-Fi wireless network coverage.
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    Erosion Potential Estimation by Network Measurement of Soil Properties in Coastal Areas after Clearcutting (2015)
    Hindawi
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    Publication Date: 2015-06-09
    Description: Invasive white leadtrees (Leucaena leucocephala (Lam.) de Wit) are contributing to the destruction of coastal ecosystems and biodiversity in humid subtropical and tropical regions. Sudden clearcutting of invasive tress can lead to substantial soil loss, which subsequently reduces the efficiency when indigenous vegetation is restored. Soil samples () were collected using the grid method to measure soil properties and to spatially analyze the soil erosion potential in the studied area after clearcutting of the invasive trees. Results indicated that the soil erosion rates ranged from 21 to 249 tons ha−1 yr−1, and the eroded soil depths ranged from 0.30 to 3.40 cm yr−1 after clearcutting. The network measurements for determining the mortality ratio of the restored indigenous vegetation demonstrated that Ficus benjamina L., Macaranga tanarius, and Scaevola taccada (Gaertner) Roxb were likely to be susceptible to damage from the substantial amount of soil loss and low SOC content. During the period between clearcutting and establishing the next stand of plants for reforestation, the network measurements for determining the soil properties and estimating the spatial heterogeneity of soil erosion potential are regarded as a major issue of concern regarding the efficiency of subsequent restoration efforts.
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    A Hybrid Algorithm of GA + Simplex Method in the WSN Localization (2015)
    Hindawi
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    Publication Date: 2015-07-30
    Description: Localization provides the key support for wireless sensor networks (WSNs). In order to solve the large-error problem in the third phase and the poor position accuracy of the least square method in the weighted DV-Hop algorithm, a hybrid algorithm of GA + simplex method was proposed in this paper. The weighted DV-Hop position algorithm was applied to estimate the distance between the unknown node and the anchor node in the first and second phase. In the third phase, a hybrid genetic algorithm with the simplex method was proposed to optimize the coordinates of the unknown nodes. In the hybrid genetic algorithm, a fitness function which combined the cost function with the penalty function was built, and the simplex method was used to increase the local search ability of the algorithm. Experiments show that both of the localization accuracy and network coverage rate are improved significantly, and the hybrid algorithm of GA + simplex method is suitable for the WSN localization.
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    Data Collection for Time-Critical Applications in the Low-Duty-Cycle Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: In low-duty-cycle wireless sensor networks, wireless nodes usually have two states: active state and dormant state. The necessary condition for a successful wireless transmission is that both the sender and the receiver are awake. In this paper, we study the problem: How fast can raw data be collected from all source nodes to a sink in low-duty-cycle WSNs with general topology? Both the lower and upper tight bounds are given for this problem. We use TDMA scheduling on the same frequency channel and present centralized and distributed fast data collection algorithms to find an optimal solution in polynomial time when no interfering links happen. If interfering links happen, multichannel scheduling is introduced to eliminate them. We next propose a novel Receiver-based Channel and Time Scheduling (RCTS) algorithm to obtain the optimal solution. Based on real trace, extensive simulations are conducted and the results show that the proposed RCTS algorithm is significantly more efficient than the link schedule on one channel and achieves the lower bound. We also evaluate the proposed data collection algorithms and find that RCTS is time-efficient and suffices to eliminate most of the interference in both indoor and outdoor environment for moderate size networks.
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    ECMTADR: Energy Conservative Multitier Architecture with Data Reduction for Cluster-Based Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-03
    Description: Regarding the energy shortage problem of wireless sensor networks (WSNs), various schemes and protocols are proposed to prolong the network lifetime. Data communication is undoubtedly the most important determinant for this energy scarce network type. In this paper, we propose a sophisticated architecture comprising data reduction, load balance, and topology control. Data reduction is ensured by the parameter spatial correlation proximity range (SCPR) that can be adjusted statically at the setup phase or dynamically revised depending on the necessities in the network. Four-layer virtual architecture is applied for implementing topology control. Furthermore, network area is partitioned into fixed-size hexagonal clusters. Depending on the regions in which the clusters take place, cluster heads (CHs) are elected from the respective subregions of the clusters. Load balance is achieved by considering residual energies and distances to the sink during both CH election and data transmission stages. Aggregated data in each cluster is transmitted towards the sink by using a load balancing single-hop intercluster routing protocol instead of direct transmission as offered in LEACH. Simulation results demonstrate that the proposed architecture ECMTADR shows almost 50% better performance in terms of energy conservation and network lifetime when it is compared to LEACH and HEED.
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    A Maximal Concurrency and Low Latency Distributed Scheduling Protocol for Wireless Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: Existing work that schedules concurrent transmissions without collisions suffers from low channel utilization. We propose the Optimal Node Activation Multiple Access (ONAMA) protocol to achieve maximal channel spatial reuse through a distributed maximal independent set (DMIS) algorithm. To overcome DMIS’s excessive delay in finding a maximal independent set, we devise a novel technique called pipelined precomputation that decouples DMIS from data transmission. We implement ONAMA on resource-constrained TelosB motes using TinyOS. Extensive measurements on two testbeds independently attest to ONAMA’s superb performance compared to existing work: improving concurrency, throughput, and delay by a factor of 3.7, 3.0, and 5.3, respectively, while still maintaining reliability.
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    Design of Randomly Deployed Heterogeneous Wireless Sensor Networks by Algorithms Based on Swarm Intelligence (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: This paper reports the design of a randomly deployed heterogeneous wireless sensor network (HWSN) with two types of nodes: a powerful node and an ordinary node. Powerful nodes, such as Cluster Heads (CHs), communicate directly to the data sink of the network, and ordinary nodes sense the desired information and transmit the processed data to powerful nodes. The heterogeneity of HWSNs improves the networks lifetime and coverage. This paper focuses on the design of a random network among HWSNs. In the design of a random HWSN, this paper uses algorithms based on the binary-valued versions of swarm intelligence, such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO). The design is then considered to be an optimization problem of how many powerful and ordinary nodes will combine to minimize the network cost, while guaranteeing a desired coverage during a given period. Simulation results show the performance of each algorithm for solving the defined optimization problem.
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    An Intelligent Wireless Sensor Networks System with Multiple Servers Communication (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: For shortcomings of current smart home system and power line carrier insufficient data transferring, an intelligent sensor networks system based on intelligent gateway is studied in this paper. Smart home system includes internal network, intelligent gateway, and external network. Multiple servers are designed in gateway, which start at the same time and receive various forms of data. Then data is processed for internal network format. External network includes several modes of communication such as TCP/IP, UDP, and pipe. Internal network includes ZigBee wireless and power line carrier (PLC) communication. Power line carrier protocol is improved, and it expands data transmission capacity to accommodate communication needs of modern family. Smart home system is designed as modules, such as intelligent gateway module, power line carrier communication module, ZigBee wireless communication modules, and appliance within electric equipment. Finally this system is physically designed and verified. The smart home system introduced in this paper has easily used and has strong compatibility.
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    A Fuzzy Similarity Elimination Algorithm for Indoor Fingerprint Positioning (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Fingerprint positioning can take advantage of existing WLAN to achieve indoor locations, which has been widely studied. We analyzed the corresponding positions distribution of similar fingerprints, and then found that the fuzzy similarity between fingerprints is the root cause of the larger errors existing. According to clusters distribution feature of corresponding positions of the similar fingerprints, we proposed a -Means+ clustering algorithm to achieve fine-grained fingerprint positioning. Due to the -Means+ algorithm failing to locate the positions of outliers, we also designed a linear sequence matching algorithm to improve the outliers positioning, and reduce the impact of fuzzy similarity. Experimental results illustrate that our algorithm can get a maximum positioning error less than 5 m, which outperforms other algorithms. Meanwhile, all the positioning errors over 4 m in our algorithm are less than 2%. The positioning accuracy has been improved significantly.
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    Indoor Robot Localization Based on Multidimensional Scaling (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: In pertinence to the application of multidimensional scaling (MDS) methods in ranging-based positioning systems, an analysis is firstly conducted by the classical MDS algorithm. Modified MDS algorithm and subspace method are presented in localization application. We also depicted the unified framework and general solutions of MDS methods. However, the least square solutions under this framework are not optimal. Their performance is still related to selection of coordinate reference points. To address this problem, a minimum residual MDS algorithm based on particle swarm optimization (PSO) is proposed to derive a new solution for indoor robot localization under the unified framework. The result of analysis indicates that the performance of minimum residual MDS method is immune to selection of reference points. Furthermore, the localization accuracy for indoor robot has been enhanced by 41% as compared with the classical MDS algorithm.
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    Chirp Spread Spectrum Transceiver Design and Implementation for Real Time Locating System (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: A chirp spread spectrum (CSS) transceiver architecture for IEEE 802.15.4a is proposed and implemented. In the transmitter, the size of the read-only memory that stores CSS signal samples for the chirp modulator is reduced by removing duplicate samples among subchirps. In the receiver, a matched filter is utilized to remove the other band noise caused by the band hopping property of CSS. A robust time synchronizer and chirp demodulator based on the matched filter are proposed. Low complexity architectures of the matched filter and biorthogonal decoder are also proposed. All of the proposed architectures are implemented in the field-programmable gate array chip and verified.
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    A Cross Layer Video Transmission Scheme Combining Geographic Routing and Short-Length Luby Transform Codes (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: Video transmission is a real challenge for wireless multihop networks with high packet loss rate. This paper proposes a cross layer video transmission scheme which combines the geographic routing in network layer and the short-length Luby transform (LT) codes in transport layer. We first analyze the effect of bit error rate (BER) on the retransmission load and the effect of payload length and LT symbols size on network efficiency. Then, based on the product of the link quality and the distance from destination, we design a routing metric for geographic routing. We further propose a cross layer transmission scheme, which adaptively adjusts payload length to encapsulate short-length LT encoded symbols and selects routes based on the new routing metric. The simulation results show that our cross layer scheme can decrease the decoding overhead and the packet loss rate, while improving the video transmission quality and the network efficiency.
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    An Efficient TDOA-Based Localization Algorithm without Synchronization between Base Stations (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: An efficient localization algorithm is proposed by utilizing the time difference of arrival (TDOA) without synchronization between base stations. Generally, a TDOA-based localization algorithm requires synchronization between base stations in order to improve the accuracy of localization. Hence, correlations using wideband signals or wire connections between base stations have been used to synchronize the base stations; however, these approaches result in additional operating costs. Thus, the proposed algorithm does not require synchronization between base stations. The TDOA equations are derived by continuously varying the locations of the source and the location of a base station. The number of packets necessary for localization is also reduced. The localization performance of the proposed algorithm is verified with Monte-Carlo simulations.
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    Lifetime Optimization Algorithm with Mobile Sink Nodes for Wireless Sensor Networks Based on Location Information (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: In order to overcome the energy hole problem in some wireless sensor networks (WSNs), lifetime optimization algorithm with mobile sink nodes for wireless sensor networks (LOA_MSN) is proposed. In LOA_MSN, hybrid positioning algorithm of satellite positioning and RSSI positioning is proposed to save energy. Based on location information, movement path constraints, flow constraint, energy consumption constraint, link transmission constraint, and other constraints are analyzed. Network optimization model is established and decomposed into movement path selection model and lifetime optimization model with known grid movement paths. Finally, the two models are solved by distributed method. Sink nodes gather data of sensor nodes along the calculated paths. Sensor nodes select father nodes and transmit data to corresponding sink node according to local information. Simulation results show that LOA_MSN makes full use of node energy to prolong network lifetime. LOA_MSN with multiple sink nodes also reduces node energy consumption and data gathering latency. Under certain conditions, it outperforms MCP, subgradient algorithm, EASR, and GRAND.
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    Uncoordinated Cooperative Multihop Forwarding in 2D Highly Dynamic Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: This paper investigates cooperative forwarding in two-dimensional highly dynamic wireless networks. Unlike traditional coordinated cooperative forwarding schemes that require a large amount of neighborhood discovery and coordination information to be exchanged before making the forwarding decision, this paper proposes an uncoordinated cooperative forwarding scheme where each node determines whether or not to forward a received packet independently based on a forwarding probability determined by its own location, the locations of the destination, and the transmitter from which it receives the packet, without the costly or even impractical neighbor discovery and coordination process. Analytical results are derived for the successful transmission probability and the expected number of forwarding nodes involved in the cooperative forwarding process. On that basis, discussions are presented on the optimal forwarding probability design that meets a predesignated successful transmission probability target using minimum number of forwarding nodes. Simulations are conducted to evaluate the performance of the proposed scheme.
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    ECCT: An Efficient-Cooperative ADHOC MAC for Cluster-Based TDMA System in VANETs (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: In VANETs, a clustering algorithm can be used to partition the network into smaller segments. Therefore, the clustering algorithms provide not only limited channel contention but also fair channel access within the cluster. In addition, they also increase spatial reuse in VANETs and efficient control for the network topology. The main concern in the clustering algorithm is the cluster stability. The major challenge is to elect a cluster head and to maintain the membership of member nodes in a highly dynamic and a fast-changing topology. Therefore, the major criterion for cluster formation is to form a stable cluster. In this paper, a clustering algorithm to affect organization and cooperative ADHOC MAC for cluster-based TDMA system in VANETs (ECCT) is proposed. The cooperation is used to help a cluster head update each neighbor cluster’s information which helps each cluster head to avoid collision when two clusters move into each other’s cluster’s transmission range. This efficiently utilizes a time slot. We use the lowest-ID algorithm to achieve organization. The analytical and simulated results show that not only the average number of time slots for electing a cluster head but also total number of time slots before data can be successfully transmitted is less than the existing cluster-based TDMA system and IEEE 802.11p.
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    Robust Monitor Assignment with Minimum Cost for Sensor Network Tomography (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: In wired networks, monitor-based network tomography has been proved to be an effective technology for network internal state measurements. Existing wired network tomography approaches assume that the network topology is relatively static. However, the network topology of sensor networks is usually changing over time due to wireless dynamics. In this paper, we study the problem to assign a number of sensor nodes as monitors in large scale sensor networks, so that the end-to-end measurements among monitors can be used to identify hop-by-hop link metrics. We propose RoMA, a Robust Monitor Assignment, algorithm to assign monitors in large scale sensor networks with dynamically changing topology. RoMA includes two components, confidence-based robust topology generation and cost-minimized monitor assignment. We implement RoMA and evaluate its performance based on a deployed large scale sensor network. Results show that RoMA achieves high identifiability with dynamically changing topology and is able to assign monitors with minimum cost.
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    A Security Data Forwarding Mechanism for Sparse Social Sensor Networks (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: With the development of the Internet of Things (IoTs), various sensor networks were deployed to sense and collect data anytime and anywhere. Traditional sparse social sensor networks (SSSNs) assume that nodes are willing to help others with packet forwarding. However, real application scenarios, such as civilian SSSNs, often observe selfish behaviors. Therefore, the assumption that nodes are cooperative is not realistic in all applications. Currently, most of the existing incentive mechanisms focus on individual selfish behaviors. Little research work has addressed social selfish behavior in SSSNs. In this paper, we propose to incentivize nodes to cooperate with others by using a virtual bank mechanism. This incentive mechanism can effectively avoid individual selfish behaviors. This mechanism, however, renders unfair social distribution. That is, poverty nodes would appear in the networks and become internal threats for social SSSNs. To avoid this, we introduce the Gini coefficient to measure the inequality of the social distribution. Furthermore, by using the taxation strategy, we avoid the internal threats caused by social selfishness. To demonstrate the selfish behavior, we introduce the forwarding protocol which is based on social relations of nodes. We demonstrate the viability of our proposed methods through extensive simulation evaluations.
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    Modeling the Dynamic Evolution of the Vehicular Ad Hoc Networks under the City Scenario (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Nowadays, vehicular ad hoc network (VANET) has attracted more and more attention due to its various applications to improve the road traffic safety and efficiency. So there were plenty of exploration work and merit on the intervehicle communication, routing, and data forwarding, but it is not easy to design the efficient routing and data forwarding algorithm, because it is hard to understand the dynamic evolution of its network topology due to the fast movement of the vehicles in the network. While the network evolution structure is the key to design the optimal data forwarding strategy, hence, in this paper, we will analyze the dynamic evolution of topology characteristics based on the real data collected by the GPS devices installed on vehicles and then model the network evolution by the dynamic topology characteristics. In the end, we analyze and verify the efficiency of our model by theoretical deductions and simulations, and our model will be helpful to find more efficient routing algorithm and build the more trustable simulator of VANET.
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    A Collecting Collision Tree Protocol for RFID Tag Identification with Capture Effect (2015)
    Hindawi
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    Publication Date: 2015-09-11
    Description: Multitag identification is one of the main advantages of the radio frequency identification (RFID) system. In the RFID system, the capture effect often happens in the real environment. When the capture effect occurs, the reader will not completely identify the tags in its scope. In many RFID applications, to get the real-time number of tags, the reader identifies the tags repeatedly. In these cases, the tag in the reader’s scope is a staying tag or an arriving tag. The reader already stores the IDs of all staying tags, so it can just verify the existence of these tags to rapidly identify them. As a result, the reader can spend the main time in recognizing arriving tags. To cope with the capture effect and identify staying tags rapidly, this paper presents a collecting collision tree protocol for RFID tag identification with capture effect (CCT). In CCT, a collecting mechanism is adopted and a lot of staying tags can be recognized in a slot. What is more, the reader can identify all tags in its range when the capture effect happens. Finally, various analysis and simulation results show that CCT outperforms the existing algorithms significantly.
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    Big Data and Knowledge Extraction for Cyber-Physical Systems (2015)
    Hindawi
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    Publication Date: 2015-09-11
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    Multiple Antenna-Aided Cascaded Energy and Matched Filter Detector for Cognitive Radio Networks (2015)
    Hindawi
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    Publication Date: 2015-09-14
    Description: A new multiple antenna-aided cascaded energy and matched filter detector (MCEM) for cognitive radio networks is proposed. Our proposed scheme is equipped with multiple receive antennas employing energy efficient energy detector (ED) and reliable matched filter (MF) to mitigate the channel fading and increase the detection performance of the secondary users (SUs). Partial decisions are first made by using cascaded energy and matched filter detector (CEM) at each antenna and then the final collaborative decision is made based on those partial decisions. The probability of detection/false alarm of the proposed scheme is presented in terms of the complementary receiver operating characteristics (ROCs). The performance of MCEM scheme is explored via MATLAB simulations that implement the clear channel assessment (CCA) modules for IEEE 802.15.4. Simulation results showed that our proposed MCEM scheme improves the detection performance and is more energy efficient as compared to CEM scheme employing single antenna and other conventional schemes.
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    Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks (2015)
    Hindawi
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    Publication Date: 2015-09-15
    Description: Distributed camera networks play an important role in public security surveillance. Analyzing video sequences from cameras set at different angles will provide enhanced performance for detecting abnormal events. In this paper, an abnormal detection algorithm is proposed to identify unusual events captured by multiple cameras. The visual event is summarized and represented by the histogram of the optical flow orientation descriptor, and then a multikernel strategy that takes the multiview scenes into account is proposed to improve the detection accuracy. A nonlinear one-class SVM algorithm with the constructed kernel is then trained to detect abnormal frames of video sequences. We validate and evaluate the proposed method on the video surveillance dataset PETS.
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    Design Study for a Quasisynchronous CDMA Sensor Data Collection System: An LEO Satellite Uplink Access Technique Based on GPS (2015)
    Hindawi
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    Publication Date: 2015-09-15
    Description: With the development of the LEO satellite communication technology, highly dependable wireless communication and sensor data collection using LEO satellites have been getting much attention for emergency, marine research, and forest fire disaster in the remote region. The satellite system is expected to have the following features: rapid production, low cost, and fast construction of the satellite network. In this paper, a QS-CDMA uplink access technique in the LEO satellite is presented and discussed, which is focused on the local clocks using GPS 1PPS timing signals and the Doppler compensation for terminal uplink. The spreading code with length of 1023, which is used for the uplink preamble, selects the shift-m-sequence that can greatly reduce the MAI and increase the number of simultaneous access users. A novel analysis method for the accuracy of clock synchronization and a novel method for the estimation of Doppler shift and propagation delay are presented. These methods are used to guide the specific hardware implementation of the QS-CDMA LEO satellite sensor data collection system. Through simulations and experiments, it results in that this system structure can drastically reduce the complexity in implementing the acquisition in the satellite and increase the adaptability of the satellite system in different environments.
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    Energy Efficient Doppler Assisted Channel Estimation for Highly Mobile OFDM Systems (2015)
    Hindawi
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    Publication Date: 2015-09-16
    Description: The complexity of channel estimation algorithms is of critical importance in high mobility orthogonal frequency division multiplexing (OFDM) systems. To reduce the complexity of the algorithm, the existing channel estimation algorithms take advantage of the correlations between the channel coefficients. However, they do not take into account the variations of the correlations with the delay tap. In this paper, we consider the change in correlation between channel coefficients for different delay taps. By considering these variations, the number of computations needed for channel estimation can be decreased. This results in a reduction in the circuit energy. The simulation results show that the proposed scheme consumes less total energy per bit for transmission distances less than about 170 m when the mobile speed is 324 Kmph.
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    On Critical Density for Coverage and Connectivity in Directional Sensor Network over Stochastic Channels Using Continuum Percolation (2015)
    Hindawi
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    Publication Date: 2015-09-17
    Description: Sensing coverage, which is one of vital issues in the design of wireless sensor networks (WSNs), can usually interact with other performance metrics such as network connectivity and energy consumption. Whatever the metrics, the fundamental problem is to know at least how many sensor nodes are needed to maintain both sensing coverage and network connectivity. In this paper, we propose a Percolation Model on Novel Gilbert Graph (PM-NGG) to obtain the critical density at which the network can become fully covered and connected considering the similarity between the occurrence of percolation and the formation of a covered and connected network. The PM-NGG is based on directional sensor network where sensors are assigned a determined sensing direction with angular intervals varying from 0 to 2π. Furthermore, we define the sensing and communication model in directional sensor network in presence of channel randomness including deterministic path attenuation, shadow fading, and multipath fading. Besides, we discuss the coverage and connectivity together as a whole under the proposed model. It is worth mentioning that the theoretical analysis and simulation results of the relationship between critical density and transmitting power give insights into the design of directional sensor network in practice.
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    Radiometric Wireless Sensor Network Monitoring of Partial Discharge Sources in Electrical Substations (2015)
    Hindawi
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    Publication Date: 2015-09-18
    Description: A wireless sensor network (WSN) with the potential to monitor and locate partial discharge (PD) in high-voltage electricity substations using only received signal strength (RSS) is proposed. The advantages of an RSS-based operating principle over more traditional methods (e.g., time-of-arrival and time-difference-of-arrival) are described. Laboratory measurements of PD that emulate the operation of a PD WSN are presented. The hardware architecture of a prototype PD WSN is described and the particular challenges of an RSS-based location approach in an environment with an unknown, and spatially varying, path-loss index are discussed. It is concluded that an RSS-based PD WSN is a plausible solution for the monitoring of insulation integrity in electricity substations.
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    Optimal Design for One-Dimensional ALOHA Ad Hoc Networks Based on Stochastic Geometry (2015)
    Hindawi
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    Publication Date: 2015-09-21
    Description: The aims of this paper are to analyze the performance of a one-dimensional ALOHA ad hoc network and to investigate the impact of the access probability of the ALOHA protocol on the network performance. As a performance metric we consider the average number of nodes that successfully receive a packet from an arbitrary node. To mathematically model the random locations of nodes and the interference in the ad hoc network, we use stochastic geometry theory. With the help of stochastic geometry theory, we model the ad hoc network, derive an analytic form of the performance metric, and finally obtain the optimal access probability that maximizes the performance metric. Numerical examples are provided to validate our analysis and to investigate the performance behavior.
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    Related-Key Differential Attacks on COSB-128 (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: COSB-128 (Moldovyan et al., 2002) is a block cipher with 128-bit and 256-bit secret keys, which use key and data-dependent operational substitutions in fast controllable permutation blocks (CPB) concept. It is designed with a simple key schedule to ensure a high speed of data transformation by fast block encryption algorithms and expected to be high stability to all known methods of cryptanalysis, especially differential and linear attacks. In this paper, we show that the COSB-128 block cipher still remains weaknesses to differential related-key cryptanalysis, by constructing two full 10-round related-key differential characteristics (DCs) of COSB-128 with high probabilities, and thence propose our two related-key differential attacks. The attacks require about 224 data and time complexities to recover 63-bit key information and 222 data and time complexities to recover 6-bit key information. This study is the first known cryptanalytic result on COSB-128 until now. From this study, the new potential for the cryptanalysis on these types of block cipher will be further revealed.
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    Energy Efficient Metadata Management for Cloud Storage System (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: To effectively handle duplicate files, data deduplication schemes are widely used in many storage systems. Data deduplication algorithms reduce storage space by eliminating data to ensure that only single instance of data is stored in storage device. In this paper, we propose an energy efficient file synchronization scheme that provides hybrid data chunking using variable-length chunking (VLC) and fixed-length chunking (FLC). The main idea is to analyze similarities between old and new versions of data and decide which chunking method to apply in synchronizing the files. In particular, the proposed algorithm exploits the file similarity pattern for calculating the energy efficiency of chunking algorithms. We have developed an Android mobile application for file synchronization and measured energy consumption. The experiment results show that the proposed scheme helps save energy in synchronizing files, regardless of file types or amount of redundancies the files have.
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    A Study on Industrial Security Experts Demanding Forecasting in Intelligent Sensor Network (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: There have been efforts made to come up with a solution through advancement based on developing technological solution. However, it has come to the point where various forms of the leakage centering on people that are the subject of core asset leakage cannot be solved through technological method. At present time in which the limitation of information security that seeks technological security has been clearly revealed, there is an increasing interest in industrial security for establishing convergence security system upon understanding technological/physical/managerial security measures and establishing security strategies. Accordingly, this paper conducted an analysis on the characteristics of industrial security manpower to present a vision and systematically cultivate industrial security experts manpower for protecting core technologies of companies in intelligent sensor network. In particular, occupational cluster of industrial security experts manpower was classified, which was verified by conducting case analysis. In addition, it estimated the demand for industrial security experts manpower by substituting it to the present condition of manpower of Korea. It is expected that the result of this study will be able to be used as basic information for cultivating industrial security experts manpower in intelligent sensor network.
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    A Study on Social Issue Solutions Using the “Internet of Things” (Focusing on a Crime Prevention Camera System) (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: Many researchers in various fields are seeking solutions to such problems through political and administrative measures. However, concrete solutions have yet to be presented. Researches that seek solutions to the said problems using new technologies are increasing. In this study, a solution for changing and improving society was proposed by investigating social issue solutions and technologies centered on social organizations and systems. To do that, the types of social issues were analyzed by defining them through the analysis in the preceding studies and using a metaresearch technique. I suggested a crime prevention security system to prevent crimes in deteriorated areas. The system is integrated with the IOT, which differs from the existing manual camera.
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    Demand Forecasting Models for Medicines through Wireless Sensor Networks Data and Topic Trend Analysis (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: Demand forecasting in the biomedical area is becoming more important because of radical changes in the macroeconomic environment and consumption trends. Moreover, the need for big data analysis on data from wireless sensor networks and social media is increasing because it shows not only the rapidly changing environmental data such as fine dust concentration but also the responses of potential customers that are expected to affect the demand for a medicine. Therefore, demand forecasting models based on data analysis in wireless sensor networks and topic modeling of buzzwords in blog documents were suggested in this study. First, we analyzed topics of documents from blogs that describe the symptoms of certain diseases related to selected medicines. Thereafter, we extracted topic trends for a selected period and constructed demand forecasting models that consist of topic trends, environmental data from wireless sensor networks, and time-series sales data. The experiment results show that topic trends about medicines significantly affect the performance of demand forecasting for these medicines.
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    Survey for Sensor-Cloud System from Business Process Outsourcing Perspective (2015)
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    Publication Date: 2015-09-28
    Description: Cloud computing is a new IT trend to meet the new business requirements such as business agility and operational efficiency with business process outsourcing (BPO). Sensor-Cloud infrastructure is the extended form of cloud computing to manage the sensors which are scattered throughout the network. Several benefits of adopting cloud computing including cost saving, high scalability, and business risk reductions also can be applied to sensor data collection. As a first investment for new technology, we analyze IT managers’ feedbacks to identify the most important factors of decision making for cloud platform adoption and IT outsourcing. Even though the technological motivation is persuasive in Korean IT market, survey results show that the cost efficiency is the most important for cloud platform adoption. Also surveys reveal that IT service consumers have difficulties understanding complicated service contracts and data sharing issues with infrastructure providers, which serve as main blockers of adopting cloud computing.
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    Automated Verification Methodology of Security Events Based on Heuristic Analysis (2015)
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    Publication Date: 2015-09-28
    Description: We present an automated verification methodology of the security events, that is, IDS alerts, based on heuristic analysis. The proposed verification methodology aims to automatically identify real cyberattacks from the security events and filter out false positive, so that the security analyst is able to conduct security monitoring and response more effectively. For the proposed verification methodology, we used the 1,528,730,667 security events that were obtained from Science and Technology Security Center (S&T-SEC). We then extracted the core security events that were caused by the real cyberattacks. Among the core security events, we selected the top 20 types of the security events in the number of the real attacks that they raised. By analyzing the top 20 types of the security events, we discovered essential elements and optional elements for using in the automated verification of the security events. The evaluation results showed that the proposed verification methodology could contribute to the reduction (about 67%) of the meaningless security events. Furthermore, we demonstrated that the proposed verification methodology contributed to the detection of 140 true negatives that were not identified by the security analyst and the total accuracy of the proposed verification methodology was 96.1%.
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    Toll Fraud Detection of VoIP Service Networks in Ubiquitous Computing Environments (2015)
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    Publication Date: 2015-09-28
    Description: Voice over Internet Protocol (VoIP) is an emerging communication service that has advanced in ubiquitous computing environments. Although VoIP is inexpensive and offers additional services, there has been little provision for attacks at the weak points. With the advances of Wireless Sensor Network (WSN) technologies, the risk is increasing. Due to the resource constraints of WSN, attacks have become easier, making protection of the network more difficult. In this work, we attempt to distinguish fraud call attacks as outliers from normal calls on the basis of call detail records. We adopted and applied a Local Outlier Factor (LOF) method on real call data, which include actual fraud call attacks. Our results show the outlier detection method can be effective in detecting fraud calls. Moreover, introducing two additional attributes related to fraud call characteristics enhanced the detection performance.
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    Self-Cancellation of Interchannel Interference for OFDM Systems in Amplify-and-Forward Relay Communication Networks (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: We propose a method to compensate the effects of multiple carrier frequency offsets (CFOs) for orthogonal frequency division multiplexing (OFDM) systems. The multiple CFOs, we considered, are caused by several spatially separated frequency-unsynchronized transmitters as in amplify-and-forward relay communication networks or wireless ad hoc sensor networks. Despite its appealing features, OFDM is extremely sensitive to CFO, especially to multiple CFOs. At the receiver, the residual CFO which appears due to incomplete compensation of multiple CFOs destroys orthogonality among subcarriers and brings interchannel interference (ICI). In the proposed scheme, we compensate the CFOs of the received signal by the predesigned value, which results in cancellation of the opposite ICI by each other. This is based on the property that the spectrum of ICIs shown in a subcarrier has similar magnitudes and opposite signs from the fact that spectrum shapes of the ICI are of sinc function. Simulation results are shown to demonstrate the effectiveness of the proposed method.
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    Secure Key Distribution Using Fragmentation and Assimilation in Wireless Sensor and Actor Networks (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: Secure key distribution is one of the most important building blocks to ensure confidentiality in wireless sensor and actor networks (WSANs). However, the key distribution becomes a challenging task when keys have to be relayed by compromised nodes in order to establish secure communication between distant nodes. To deal with this issue, we propose in this paper a key distribution scheme, named key distribution using fragmentation and assimilation (KDFA). In this scheme, the sender node splits the actual key into fragments and sends them through intermediate actor nodes towards the receiver node. The latter assimilates these key fragments using XOR operation to reconstruct the actual key. In this case, attacker cannot retrieve the actual key and only gets the key fragment. KDFA is composed of two parts: (a) key distribution protocol (KDP) to distribute the key using intra-actor and interactor communication scenarios and (b) key fragmentation algorithm (KFA) to slice the key using binary calculations. KDFA execution has been specified and formally verified using Rubin logic. Moreover, the performance and the resilience of the proposed protocol are further analyzed through extensive simulations using ns-2.35. Results show that KDFA is resilient against actor node compromise and key exposure.
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    A Study of K-ISMS Fault Analysis for Constructing Secure Internet of Things Service (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: Although Internet of Things (IoT) technologies and services are being developed rapidly worldwide, concerns of potential security threats such as privacy violation, information leak, and hacking are increasing as more various sensors are connected to the Internet. There is a need for the study of introducing risk management and existing security management standard (e.g., ISO27001) to ensure the stability and reliability of IoT services. K-ISMS is a representative certification system that evaluates the security management level of the enterprise in Korea and is possible to apply as a standardized process to enhance the security management of IoT services. However, there are growing concerns about the quality deterioration of the K-ISMS certification assessment these days because of internet security incidents occurring frequently in K-ISMS certified enterprises. Therefore, various researches are required to improve the accuracy and objectivity of the certification assessment. Since existing studies mainly focus on simple statistical analysis of the K-ISMS assessment results, analysis on the cause of certification assessment fault based on past data analysis is insufficient. As a method of managing the certification inspection quality, in this paper, we analyze the association among the fault items of the K-ISMS certification assessment results using association rule mining which involves identifying an association rule among items in the database.
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    A Personal Credit Rating Prediction Model Using Data Mining in Smart Ubiquitous Environments (2015)
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    Publication Date: 2015-09-28
    Description: This study suggests a methodology called a smart ubiquitous data mining (UDM) that consolidates homogeneous models in a smart ubiquitous computing environment. It tests the suggested model with financial datasets. It basically induces rules from the dataset using diverse rule extraction algorithms and combines the rules to build a metamodel. This paper builds several personal credit rating prediction models based on the UDM and benchmarks their performance against other models which employ logistic regression (LR), Bayesian style frequency matrix (BFM), multilayer perceptron (MLP), classification tree methods (C5.0), and neural network rule extraction (NR) algorithms. To verify the feasibility and effectiveness of UDM, personal credit data and personal loan data provided by a Financial Holding Company (FHC) were used in this study. Empirical results indicated that UDM outperforms other models such as LR, BFM, MLP, C5.0, and NR.
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    Observations of Device Orientation Decisions on Mobile Videos (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: A sensor-rich mobile video represents a new type of videos acquired from modern smart phones. During video recording, it is also recorded various amounts of sensor data collected from embedded sensors. Unlike the conventional videos acquired from proprietary capturing devices, these videos allow enriched reconstruction of their surrounding environments, while enabling users to record them handily. In this paper, we examine the robustness of existing device orientation detection method, by analyzing the motion sensor samples that are publicly available from the sensor-rich mobile video hosting website, and discuss our observation results and potential problems when computing device orientation of georeferential mobile videos.
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    Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: For a hybrid sensor network, the effective coverage rate can be optimized by adjusting the location of the mobile nodes. For many deployments by APF (artificial potential field), due to the common problem of barrier effect, it is difficult for mobile nodes to diffuse by the weaker attraction when the nodes initially distribute densely in some places. The proposed deployment algorithm PFPSO (Potential Field-Directed Particle Swarm Optimization) can overcome this problem and guide the mobile nodes to the optimal positions. Normally the requirement is different for the effective coverage rate between the hotspot area and the ordinary area. On the basis of PFPSO, NPFPSO (Nonuniform PFPSO) algorithm was also proposed to implement nonuniform coverage according to the importance degree of the monitoring area. Simulation result illustrates that PFPSO algorithm can effectively improve the effective coverage rate of the network, and NPFPSO algorithm can obtain a balanced result of effective coverage rate for both hotspot area and ordinary area.
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    Design and Implementation of the Natural Light Reproduction System Based on Context Awareness in WSN (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: Changes in natural light in the daily cycle and monthly cycle and its seasonal changes create rhythms in bodies of living creatures including humans. The circadian rhythm connected to natural light stimulates psychological states and hormonal changes. As such, natural light is a major environmental factor that affects humans’ psychological and physiological conditions. To create healthy and comfortable lighting environments in windowless space such as a basement where no natural light can enter, the daily, monthly, and seasonal cycles of natural light need to be represented by means of artificial lightings. Upon certain situations related to purposes of space and user behaviors, lighting control technology is required for appropriate lighting environments. To this end, this study designs and implements a natural light reproduction system based on context awareness in wireless sensor networks to restructure lighting environments in adaptation to the changing situation of the occupant. As the object space in the experiment, a clothing shop to occupy the largest portion of underground space was selected. The scenarios were selected for each time period in connection with the behaviors of the seller who resided there for a long time. The suggested system’s performance was evaluated in terms of conformity with natural light, comfort, and energy-saving effect.
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    The Information Filtering of Gene Network for Chronic Diseases: Social Network Perspective (2015)
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    Publication Date: 2015-09-28
    Description: Web and mobile platforms have provided an environment of technical cooperation through technical development and the diffusion of related devices. Large-scale data sets have been available to analyze web interaction and data analysis. Particularly, large-scale data make us learn new patterns and insight into several research fields. For healthcare field, most chronic diseases are caused by environmental and genetic factors (Van der Laan et al., 2003). The relationship between environmental exposure and gene factors is crucial regarding disease etiology (Swift et al., 2004). For example, Tobacco is considered one of the biggest environmental factors responsible for many diseases each year. Schwartz and Collins (2007) discussed the importance of gene and environment factor correlation in human diseases. Thomas (2010) published a review of different approaches on gene-environment association studies attempting to explain some of the most complex diseases. Although previous studies have studied chronicle diseases with their causes one by one, those studies do not show integrated relationships between various diseases and their related human genes. Therefore, this study investigates the gene-disease relationships which are affected by tobacco and is able to find new association links with social network analysis and other mining techniques.
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    Knowledge Management Technologies for Collaborative Intelligence: A Study of Case Company in Korea (2015)
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    Publication Date: 2015-09-28
    Description: To create wide and deep knowledge flows by providing implicit and explicit knowledge services, organizations have constructed knowledge management systems (KMS). As employees are major knowledge resources in an organization, it is essential to use their collaborative intelligence in KMS, but there has been little research on how the heterogeneous networks of people interact to produce intelligent outcomes. This research suggests a new KM framework that leverages collaborative intelligence techniques, such as collaborative search, collaborative filtering, and social network analysis, as well as conventional knowledge management techniques including smart sensor technology. Finally, this paper reports our experience in a real world KMS development case that applied the framework and suggests challenges of knowledge management learned from this research.
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    A Hybrid Prediction Model for Monitoring of River Water Quality in the USN System (2015)
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    Publication Date: 2015-09-28
    Description: River water quality is directly related to the wellness of its neighbors. Because the West Nakdong River has long suffered both from the infiltration of sea water and from the inflow of turbid wastewater, inconsiderate use of this water can cause disastrous result to nearby agricultural areas and neighbors. Busan city in Korea had deployed a pilot USN (ubiquitous sensor network) system that monitors this river and nearby tube wells to properly react to those situations. In this paper, we have designed a system that predicts salinity level of groundwater while monitoring the electrical conductivity (EC) values of sensors in that USN. We use a hybrid method that combines pattern-based approach together with statistical regression model to analyze sensor data. After classifying past sensor outputs into several characteristic patterns, we trace each day’s change to identify base pattern of that day and thus predict the next value of sensor output. Since the detection of each day’s pattern takes some time, we need to incorporate statistical regression model as an interim prediction method. Through an experiment that compares the hybrid model to previous statistical regression model, we have shown that our hybrid model is more accurate to predict the sensor’s movement.
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    A Real-Time Video Watermarking Algorithm for Authentication of Small-Business Wireless Surveillance Networks (2015)
    Hindawi
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    Publication Date: 2015-09-28
    Description: In some business applications, all kinds of cameras sensors are employed in a distributed way to capture videos for different tasks such as surveillance. Once some illegal actions happen, then somebody or some organization wants to forge or replace some surveillance video clips to destroy evidences or obtain illegal profits. How to authenticate the genuineness and integrity of the source video or trace the source of a video information leak becomes a growing requirement in these small businesses. Fortunately, video watermark just provides an effective technology to resolve this issue. This paper proposes a real-time video watermarking scheme for MPEG, where firstly exploits fast scenes segmentation to original video sequence and adaptively selects appropriate scenes to be embedded. Furthermore, visual model is utilized to modulate watermark strength. Watermarks are embedded by adjusting the number of bit1 in the bitstreams through changing level of run-level pairs. Experiment results show little loss of video quality and also exhibit excellent robustness against many attacks. As watermark is directly detected in bitstreams domain, real-time detection becomes a reality. In addition, the embedding strategy guarantees that the bit rate is not increased and the experiments also validate it.
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    CBDAC: Context-Based Dynamic Access Control Model Using Intuitive 5W1H for Ubiquitous Sensor Network (2015)
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    Publication Date: 2015-09-28
    Description: Currently, access control is facing many issues for information protection in the ubiquitous sensor network (USN) environment. In particular, dynamic access control is a central problem where context always changes because of volatile ubiquitous sensors. The use of context is important in USN. In this paper, we focus on the context-driven privacy protection model. In context-based access control research, the access permission technique that uses context is being intensely investigated because of the ease with which various dynamic access permissions can be assigned in accordance with the various changes in context. A key feature of this approach is dynamic access control. Therefore, we propose a model for privacy preservation that is context-based dynamic access control that uses intuitive 5W1H for USN. According to this model, the access control strategy can be determined dynamically based on context elements and subject attributes, in addition to objects and operations, using access control entities; therefore, it is relatively easy to infer the dynamic access control of context expressivity both accurately and efficiently.
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    An RSA-Like Scheme for Multiuser Broadcast Authentication in Wireless Sensor Networks (2015)
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    Publication Date: 2015-09-29
    Description: For network users roaming in a wireless sensor network (WSN), they can broadcast queries to WSNs to obtain the latest sensed data from sensor nodes using their mobile devices. In such a scenario, each sensor node has to verify the validity of every query sent from users. In this paper, RSA-like public key cryptography is employed to design a mechanism for multiuser broadcast authentication in WSNs. Within the proposed scheme, the use of certificates becomes optional. When users broadcast queries to WSNs, each sensor node can verify every query immediately without buffering any one. As a result, the energy cost for verifying a query by a sensor node is very small. Furthermore, our scheme provides enough scalability and security. The quantitative analyses show that our scheme is efficient in terms of storage and computational overheads.
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    Enabling Technologies for Next-Generation Sensor Networks: Prospects, Issues, Solutions, and Emerging Trends (2015)
    Hindawi
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    Publication Date: 2015-11-23
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    Efficient Aerial Data Collection with UAV in Large-Scale Wireless Sensor Networks (2015)
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    Publication Date: 2015-11-23
    Description: Data collection from deployed sensor networks can be with static sink, ground-based mobile sink, or Unmanned Aerial Vehicle (UAV) based mobile aerial data collector. Considering the large-scale sensor networks and peculiarity of the deployed environments, aerial data collection based on controllable UAV has more advantages. In this paper, we have designed a basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network. We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal of a Fast Path Planning with Rules (FPPWR) algorithm based on grid division, to increase the efficiency of path planning, while guaranteeing the length of the path to be relatively short. We have designed and implemented a simulation platform for aerial data collection from sensor networks and have validated performance efficiency of the proposed framework based on the following parameters: time consumption of the aerial data collection, flight path distance, and volume of collected data.
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    FloorLoc-SL: Floor Localization System with Fingerprint Self-Learning Mechanism (2015)
    Hindawi
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    Publication Date: 2015-11-24
    Description: Nowadays, a mobile phone plays an important role in daily life. There are many applications developed for mobile phones. Location service application is one kind of mobile application that serves location information. GPS receiver is embedded on a mobile phone for localization. However, GPS cannot provide localization service over indoor scenario efficiently. This is because obstacles and structures of building block GPS signal from the satellites. Many indoor localization systems have been proposed but most of them are developed over single-floor scenario only. The dimension of altitudes in localization results will be missed. In this paper, we propose floor localization system. The proposed system does not need any site survey and any support from back-end server. It has a self-learning algorithm for creating fingerprint in each floor. The self-learning algorithm utilizes sensors on the mobile phone for detecting trace of mobile phone user. This algorithm is low computation complexity, which can be operated on any mobile phones. Moreover, the mobile phone can exchange fingerprints with others via virtual ad hoc network instead of learning all floor fingerprints by themselves only. Our proposed floor localization system achieves 87% of accuracy.
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    Experiencing Commercialized Automated Demand Response Services with a Small Building Customer in Energy Market (2015)
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    Publication Date: 2015-11-26
    Description: An Automated Demand Response is the most fundamental energy service that contributes to balancing the power demand with the supply, in which it realizes extensive interoperations between the power consumers and the suppliers. The OpenADR specification has been developed to facilitate the service communications, and several facilities offer primitive forms of services in a retail market. However, few researches have reported the details of such a real-world service yet, and thus we are still unaware of how it works exactly. Instead, we rely on our textbooks to design next generations of the ADR service. To overcome the discrepancy of our understanding, this paper shares our hand-on experiences on the commercialized ADR service. In particular, we deploy smart submeters to manage energy loads and install an energy management system in a small commercial facility, helping the owner participate in the ADR service that a local utility offers. The building owner makes a service contract with a qualified load aggregator based on her curtailment rate, a reference point that decides the success of her load curtailment. With the rate, the customer facility participates in three DR events for tests that last for 2, 1, and 3 hours, respectively. Our experimental results are illustrated with discussions on various aspects of the service.
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    Mixed and Continuous Strategy Monitor-Forward Game Based Selective Forwarding Solution in WSN (2015)
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    Publication Date: 2015-11-26
    Description: Wireless sensor networks are often deployed in unattended and hostile environments. Due to the resource limitations and multihop communication in WSN, selective forwarding attacks launched by compromised insider nodes are a serious threat. A trust-based scheme for identifying and isolating malicious nodes is proposed and a mixed strategy and a continuous strategy Monitor-Forward game between the sender node and its one-hop neighboring node is constructed to mitigate the selective dropping attacks in WSN. The continuous game will mitigate false positives on packet dropping detection on unreliable wireless communication channel. Simulation results demonstrate that continuous Monitor-Forward game based selective forwarding solution is an efficient approach to identifying the selective forwarding attacks in WSN.
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    Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing (2015)
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    Details
    Publication Date: 2015-11-26
    Description: The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. However, the sparsity of raw sensed data in some case is not straightforward. In this paper, we present reshuffling cluster compressed sensing based data gathering (RCCSDG) method to achieve both energy efficiency and reconstruction accuracy in WSNs. By incorporating CS into the cluster protocol, RCCSDG is able to reduce the energy consumption and support larger networks. Moreover, the sparsity of raw sensed data can be greatly improved by reshuffling pretreatment. A theoretical analysis to energy consumption of cluster head is performed, and the cost of the pretreatment is small enough to be neglected. Based on these natures, the raw sensed data can be recovered from fewer samples. Also, considering the sensed data to be of excellent temporal stability in a short time, we reshuffle them just one time in this stable period to further reduce the energy consumption of WSNs. In addition, the delay of RCCSDG is analyzed based on TDMA2 scheduling scheme. We carry out simulations on real sensor datasets. The results show that the RCCSDG can effectively compress the data transmission and decrease energy consumption of WSNs while ensuring the reconstruction accuracy.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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    Real-Time Monitoring and Early Warning Method Utilizing FBG Sensors in the Retrofitting Process of Structures (2015)
    Hindawi
    Details
    Publication Date: 2015-08-27
    Description: Associated with a project, the application of real-time monitoring and early warning system in the retrofitting process of structures was investigated. Based on the software ANSYS, structural analysis and thermal analysis were carried out to determine the distribution of sensors and the early warning threshold value in monitoring process. SHM system was developed for damage sensing in real-time using FBG sensors. Eight FBG sensor clusters consisting of a strain sensor and a temperature sensor were welded on the steel beam surface. Using these FBG sensors, the real-time strains in key positions during the cutting process of steel beam were measured. The monitoring data provided the early warnings and effective reference for analyzing the stability of steel beam in real-time.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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    A Novel Hybrid Anticollision Algorithm for RFID System Based on Grouped Dynamic Framed Recognition and Binary Tree Recursive Process (2015)
    Hindawi
    Details
    Publication Date: 2015-08-27
    Description: Recently, RFID technology has come into end-user applications for monitoring, tracking, and so forth. In RFID system, a reader identifies a set of tags over a shared wireless channel. When multiple tags communicate with the same reader simultaneously, all packages will be lost and no tag can be recognized, which is known as tag collision. Tag collision is a significantly important issue for fast tag identification. We firstly make a thorough analysis among a variety of traditional RFID anticollision algorithms. Then a novel hybrid anticollision algorithm called T-GDFSA is proposed. Tags are assigned to different groups based on the initial tag estimation and then experience several dynamic read frames for identification. When a collision occurs in current slot, a tree-based recursive process will be deployed immediately. T-GDFSA combines the advantages of ALOHA-based and tree-based together and acquires higher system throughput by reducing unnecessary idle and collision slots and lower communication complexity by decreasing the data transmitted, which makes it identify tags faster with less power consumption. Simulations show that the theoretical values match well the simulation results. Moreover, T-GDFSA also has a good tolerance for the inaccuracy of initial tag estimation and the length variation of tag’s ID.
    Print ISSN: 1550-1329
    Electronic ISSN: 1550-1477
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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