ALBERT

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉In order to resolve the issue of coverage limitation for the future fifth-generation network, deploying a relay node within a cell is one of the most capable and cost-effective solution, which not only enhances the coverage but also improves the spectral efficiency. However, this solution leads to the undesired interferences from nearby base station and relay nodes that affects user’s signal-to-interference-plus-noise ratio and can cause the ambiguous received signal at the user end. In this article, we have analyzed a relay-based interference-limited network at millimeter wave frequency and proposed a Poisson point process–based model using a stochastic geometrical approach. The results for the proposed Poisson point process model have been evaluated in terms of success probability, network ergodic capacity, and outage probability, compared with the ideal grid model and conventional multiple-antenna ultra-dense network model. The results proved that the success probability and ergodic capacity for the proposed model are 3.5% and 2.3% higher as compared to the most commonly used model for the high-density network, respectively. Furthermore, the results have been analyzed at different multiple-input-multiple-output antenna configuration, which validates the model in the improvement of overall network performance even for higher number of antennas.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Multi-hop wireless sensor networks are widely used in many location-dependent applications. Most applications assume the knowledge of geographic location of sensor nodes; however, in practical scenarios, the high accuracy on position estimates of sensor nodes is still a great challenge. In this research, we propose a hop-weighted scheme that can be useful in distance-based distributed multi-hop localization. The hop-weighted localization approach generates spatial locations around position estimates of unknown sensors and computes local functions that minimize distance errors among hop-weighted and static neighboring sensors. The iterative process of each unknown sensor to re-estimate its own location allows a significant reduction of initial position estimates. Simulations demonstrate that this weighted localization approach, when compared with other schemes, can be suitable to be used as a refinement stage to improve localization in both isotropic and anisotropic networks. Also, under rough initial position estimates, the proposed algorithm achieves root mean square error values less than the radio range of unknown sensors, in average, with only a few iterations.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Due to the increased demand of wireless sensor networks for their characteristics like low energy consumption, robustness, and low cost in several demanding and complex applications like smart grid, health and safety, traffic and weather updates, there is need of monitoring the infrastructure in a timely manner with high reliability. In this article, a cross-layer data communication scheme target-aware cross-layer technique is proposed to enhance reliability and to reduce the latency in wireless sensor networks. The proposed scheme uses connected dominating set at network layer where nodes in the connected dominating set are directly connected to all the other nodes in the network. Each sensor node sends the data to the nodes present in the connected dominating set, which forwards it to their respective destinations. The proposed scheme reduces the chances of collision resulting reduced delays. Higher packet delivery ratio is achieved with the proposed scheme results in improved reliability. The proposed scheme is outperforming other state-of-the-art schemes in terms of packet delivery ratio, latency, and data throughput with the default 802.15.4 and delay-responsive cross layer in both static and mobile scenarios using network simulator tool.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉In this article, we present a sensitivity-enhancing feedback control–based damage detection method for piezoelectric actuator and sensor bonded composite laminates with delamination failures. The present method mainly consists of two parts: delamination modeling and feedback controller design. We first introduce the adopted improved layerwise theory–based mathematical model for delamination modeling with finite element implementation. The obtained second-order governing equations are transformed into the state space model for design of state feedback controller. Proper pole placement is required to enhance the sensitivity of frequency shifts to stiffness change caused by delamination. We investigated different delamination interfaces and longitudinal locations for studying the feasibility and efficiency of the present method. The present results clearly demonstrate that with the applied state feedback controller, the frequency shifts of the closed-loop system are significantly enhanced. The proposed sensitivity-enhancing feedback control can be used as an efficient tool for detecting delamination failures in smart composite structures.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉With the continuous development of Internet of things, all kinds of smart systems are quickly evolving to make our day-to-day life smoother and safer. Like many other sectors, transportation has entered a period of rapid change. Intelligent Traffic System is one of the fastest-growing fields within the smart systems, which is expected to increase road safety, mitigate traffic congestion, and enable fuel efficiency. The main functionalities of Intelligent Traffic System are as follows: (1) monitoring real-time traffic conditions in specific areas, (2) locating traffic emergencies (i.e. traffic accidents) in specific areas, and (3) dynamic monitoring and managing the continuous use in public transit services (i.e. change in car lanes) that may lead to changes in macro traffic conditions. This article will use the above-mentioned functionalities of the Intelligent Traffic System as underlying simulative scenarios, to design and to implement a smart transportation system based on Internet of things and blockchain—both share inherent distributed technology characteristics—combining both Internet of things sensor nodes and distributed ledger technology, to (1) record the changes in intelligent transportation systems and (2) set up a credit-token mechanism for paying the use and misuses in public transit services accordingly. The Intelligent Traffic System described in this article is intended to be used as experimental project only, given the terms and conditions as depicted in the simulated scenario. In real-life traffic scenarios, it may generate more complex system and data security issues, which will be elaborated and analyzed at the end of this article. Intelligent Traffic System is a comprehensive smart system; it can significantly change and reinvent the wheel for traffic conditions. Based on the system development as discussed in this article, there are still a lot of demands and challenges that need to be addressed in the future. Such topic scope will be explored in depth in our subsequent research.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉In the context of fingerprinting applications, this article presents the performance analysis of a type of space labeling based on the binary quantization of the received signal strength indicator. One of the common drawbacks of fingerprinting is the large data size and consequently the large search space and computational load as a result of either vastness of the positioning area or the finer resolution in the fingerprinting grid map. Our approach can be considered, for example, when we use very small, inexpensive beacons, like those based on bluetooth low energy technology, radio frequency identification, or in the future context of the Internet of Things. One of the interesting properties of this deployment is that it can be interpreted as a form of space labeling or encoding since space is divided into cells, and each cell is associated to a binary codeword with the corresponding scalability of the spatial resolution. Here, it developed the performance estimation, exploiting the association of this deployment to an error correcting code. The analysis and numerical and experimental results allow a deeper understanding of the impact of the proposed solution and show that it is robust and computationally efficient with respect to the traditional fingerprinting technique.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉Accurately predicting the load change of the information system during operation has important guiding significance for ensuring that the system operation is not interrupted and resource scheduling is carried out in advance. For the information system monitoring time series data, this article proposes a load trend prediction method based on isolated forests-empirical modal decomposition-long-term (IF-EMD-LSTM). First, considering the problem of noise and abnormal points in the original data, the isolated forest algorithm is used to eliminate the abnormal points in the data. Second, in order to further improve the prediction accuracy, the empirical modal decomposition algorithm is used to decompose the input data into intrinsic mode function (IMF) components of different frequencies. Each intrinsic mode function (IMF) and residual is predicted using a separate long-term and short-term memory neural network, and the predicted values are reconstructed from each long-term and short-term memory model. Finally, experimental verification was carried out on Amazon’s public data set and compared with autoregressive integrated moving average and Prophet models. The experimental results show the superior performance of the proposed IF-EMD-LSTM prediction model in information system load trend prediction.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉The coverage intensity of sensors is the most important issue on structural health monitoring technique. The geometric configuration of sensors must be optimized based on coverage intensity with proper objectives. In this article, a novel algorithm for optimal sensor placement in various steel frames was evaluated. These frames including moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall were selected for case studies. This approach was proposed based on combination of common optimal sensor placement algorithm and nonlinear time history analysis. A new method called transformed time history to frequency domain approach was evaluated to transform nonlinear time history analysis results to frequency domain and then the effective frequencies according the maximum range of Fourier amplitude were selected. The modified type of modal assurance criterion values can be achieved from modal assurance criterion with the exact seismic displacement. All of novel optimal sensor placement processes were done through FEM-MAC-TTFD code modeled and developed in MATLAB by authors of this article. The results show that there is good relative correlation between the sensors number and coverage intensity obtained with modal and modified modal assurance criterion approaches for moment-resisting frame system, but for integrated frame such as moment-resisting frame with base isolation and moment-resisting frame with base isolation with steel shear wall, the modified modal assurance criterion approach is better approach. There is no significant difference between coverage intensity of sensors for top joints between modal assurance criterion and modified modal assurance criterion approaches for moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall systems (R2 = 0.994, 0.986, and 0.724, respectively). It was found that if reference point is located in center of frame, there is significant difference between modal assurance criterion and modified modal assurance criterion approaches, and modified modal assurance criterion generated slightly better results.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉It is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information fusion into light field reconstruction to monitor and recognize the maneuvering targets. First, the light field is represented as sub-light fields at different perspectives (i.e. the Multi-sensor distributed network), and sparse representation and reconstruction are then performed. Second, we establish the multi-perspective distributed information fusion under the condition of regional full-coverage constraints. Finally, the light field data from multiple perspectives are fused and the states of the maneuvering targets are estimated. Experimental results show that the light field reconstruction time of the proposed method is less than 583 s, and the reconstruction accuracy exceeds 92.447% compared with the existing spatially variable bidirectional reflectance distribution function, micro-lens array, and others. In the aspect of maneuvering target recognition, the recognition time of the algorithm in this article is no more than 3.5 s. The recognition accuracy of the algorithm in this article is up to 86.739%. Moreover, the more viewing angles used, the higher the accuracy.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Wireless sensor networks have drawn tremendous attentions from all fields because of their wide application. Maximizing network lifetime is one of the main problems in wireless sensor networks. This article proposes an energy-efficient routing protocol which adopts unequal clustering technology to solve the hot spots problem and proposes double cluster head strategy to reduce the energy consumption of head nodes in the clusters. In addition, to balance the energy consumption between cluster heads and cluster members, a hybrid cluster head rotation strategy based on time-driven and energy-driven is proposed, which can make the timing of rotation more reasonable and the energy consumption more efficient. Finally, we compare the proposed protocol with LEACH, DEBUC, and UCNPD by simulation experiments. The simulation results prove that our proposed protocol can effectively improve the performance in terms of network lifetime, energy consumption, energy balance, stability, and throughput.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Wireless sensor networks require time synchronization, which is the coordination of events or actions to make a system operate in unison. In this work, real experiments and a theoretical analysis of the behavior of the clock sources, most used in wireless sensor networks, have been carried out. The experiments have been performed on two real platforms from two different manufacturers in real environments with sudden changes in temperature. Complementary metal-oxide-semiconductor oscillators have a low accuracy, bigger than 500 ppm, and a high dependency with temperature. External crystal oscillators have good accuracy, around 20 ppm, and are stable with temperature. Temperature-compensated crystal oscillators are very accurate, around 5 ppm, and the temperature has no influence in their drift. The use of phase-locked loop circuits minimizes the impact of temperature and stabilizes oscillators. We highlight and demonstrate the importance of the early stages of design, especially the selection of the clock source, because that decision has a great impact on the performance of the time synchronization in wireless sensor networks.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Smart grids have recently attracted increasing attention because of their reliability, flexibility, sustainability, and efficiency. A typical smart grid consists of diverse components such as smart meters, energy management systems, energy storage systems, and renewable energy resources. In particular, to make an effective energy management strategy for the energy management system, accurate load forecasting is necessary. Recently, artificial neural network–based load forecasting models with good performance have been proposed. For accurate load forecasting, it is critical to determine effective hyperparameters of neural networks, which is a complex and time-consuming task. Among these parameters, the type of activation function and the number of hidden layers are critical in the performance of neural networks. In this study, we construct diverse artificial neural network–based building electric energy consumption forecasting models using different combinations of the two hyperparameters and compare their performance. Experimental results indicate that neural networks with scaled exponential linear units and five hidden layers exhibit better performance, on average than other forecasting models.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Home-based multi-sensor Internet of Things, as a typical application of Internet of Things, interconnects a variety of intelligent sensor devices and appliances to provide intelligent services to individuals in a ubiquitous way. As families become more and more intelligent, complex, and technology-dependent, there is less and less need for human intervention. Recently, many security attacks have shown that Internet home-based Internet of Things have become a vulnerable target, leading to personal privacy problems. For example, eavesdroppers can acquire the identity of specific devices or sensors through public channels, which is not secure, to infer individual public life in the home area network. Authentication is the essential portion of many secure systems processing of verifying and declaring identity. Before providing confidential information, home-based-Internet of Things service authenticates users and devices. The communication and processing capabilities of intelligent devices are limited. Therefore, in home-based Internet of Things, lightweight authentication and key agreement technology are very important to resist known attacks. This article proposes an anonymous authenticated key agreement protocol using pairing-based cryptography. The protocol proposed in this article provides lightweight computation and ensures the security of communication between home-based multi-sensor Internet of Things network and Internet network.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉Using unmanned aerial vehicle as movable base stations is a promising approach to enhance network coverage. Moreover, movable unmanned aerial vehicle–base stations can dynamically move to the target devices to expand the communication range as relays in the scenario of the Internet of things. In this article, we consider a communication system with movable unmanned aerial vehicle–base stations in millimeter-Wave. The movable unmanned aerial vehicle–base stations are equipped with antennas and multiple sensors for channel tracking. The cylindrical array antenna is mounted on the movable unmanned aerial vehicle–movable base stations, making the beam omnidirectional. Furthermore, the attitude estimation method using the deep neural network can replace the traditional attitude estimation method. The estimated unmanned aerial vehicle attitude information is combined with beamforming technology to realize a reliable communication link. Simulation experiments have been performed, and the results have verified the effectiveness of the proposed method.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉The crowdsourcing schemes which utilize the social network to solve complex tasks are an important part of open cooperation over the Internet. Although blockchain-based crowdsourcing schemes have considerable advantages in decentralization and data sharing, there is still a challenge to gurantee the security of crowdsourced-sensitive information and the fairness of crowdsourcing on the blockchain. To this end, this article investigates a crowdsourcing scheme based on blockchain. First, we define the basic requirements of blockchain-based crowdsourcing schemes including fairness, confidentiality, and integrity. And then, using secure hash, commitment, and homomorphic encryption, we propose a blockchain-based secure and fair crowdsourcing scheme, that is, BFC. The analysis results show that our scheme can satisfy the above requirements. Finally, the experimental results show that the computational overhead of the BFC scheme is acceptable to both the requester and the workers. In a word, our proposed crowdsourcing scheme has good expansibility in reality.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉It has been seen that most of the accidents occur due to driver’s fatigue. Drowsiness is a state of mind before the driver falls asleep, which means the driver could not accomplish his actions, such as vehicular braking, controlling vehicular motion, properly. We have built an Internet of things–based medical application to analyze driver’s drowsiness. An architecture has been proposed and a simulation of that scenario in NS3 WSN simulation tool has been done. This simulation shows that the ratio of accidents can be majorly reduced. When drowsiness of drivers is captured, a message alert is delivered to all other drivers of the vehicles that are near to the sleeping driver; for this, different sensor nodes are used. Another unique feature of the sensor network used here is the collaborative effect of sensor nodes. So for measurement and analysis of applications on Google Play, a dataset of the medical applications category was scraped. The scraping was done with 550 applications of each category of medical applications. On each application on Google Play store, almost 70 attributes for each category were scraped. It is envisioned that, in future, wireless sensor networks will be an integral part of our lives, more so than the present-day personal computers.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉This article investigates the possibility of advancing discrete manufacturing using system architectures that are developed for Collaborative Process Automation Systems. Collaborative Process Automation System is a technology that has the potential to achieve production excellence for process industry. However, not much attention has been paid on using the architectures based on Collaborative Process Automation Systems for discrete manufacturing domains. In this article, we propose a base architecture consisting of three layers, and we discuss various alternatives to make the communications among the layers. We consider legacy components in the proposal, in contrast to most of the related works. In order to show the practicality of the proposed alternatives, we present an example that has been implemented in an ongoing project at ABB Robotics in Sweden.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉Security of cyber-physical systems against cyber attacks is an important yet challenging problem. Cyber-physical systems are prone to information leakage from the physical domain. The analog emissions, such as magnetic and power, can turn into side channel revealing valuable data, even the crypto key of the system. Template attack is a popular type of side-channel analysis using machine learning technology. Malicious attackers can use template attack to profile the analog emission, then recover the secret key of the system. But conventional template attack requires that the adversary has access to an identical experiment device that he can program to his choice. This study proposes a novel side-channel analysis for physical-domain security in cyber-physical systems. Our contributions are the following three points: (1) Major peak region method for finding points of interests correctly is proposed. (2) A method for establishing templates on the basis of those points of interest still without requiring knowledge of the key is proposed. Several techniques are proposed to improve the quality of the templates as well. (3) A method for choosing attacking traces is proposed to significantly improve the attacking efficiency. Our experiments on three devices show that the proposed method is significantly more effective than conventional template attack. By doing so, we will highlight the importance of performing similar analysis during design time to secure the cyber-physical system.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉In a multi-heterogeneous network with dense deployment and convergence environment, how to efficiently and reasonably allocate idle spectrum resources of the primary network to meet the diversified business demands of secondary users is a difficult problem. In this article, with the goal of maximizing the total transmission rate and minimizing the total cost, a dual-objective optimization mathematical model for network selection and idle spectrum allocation is established in the context of comprehensive consideration of the diversity of spectrum resource attributes and the diversification of secondary users’ business needs. Based on this, two kinds of technical paths to solve the complex network selection and spectrum allocation problem are applied in this article. The first is the simplification method. By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. And then makes a decision selection on the optimal solution set to select a compromise solution. Finally, methods proposed in this article are compared with the multi-objective artificial bee colony algorithm through experiments. Experimental results show that the simplified method has higher efficiency, and the improved non-dominated sorting genetic algorithm II can get higher transmission rate, especially the transmission rate–priority strategy.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉In the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high computing capabilities. Processing all the data in the cloud may not be sufficient in cases when we need privacy and low latency, and when we have limited Internet bandwidth, or it is simply too expensive. It poses a challenge for creating a new generation of fog computing that supports artificial intelligence and selects the architecture appropriate for an intelligent solution. In this article, we show from four perspectives, namely, hardware, software libraries, platforms, and current applications, the landscape of components used for developing intelligent Internet of Things solutions located near where the data are generated. This way, we pinpoint the odds and risks of artificial intelligence fog computing and help in the process of selecting suitable architecture and components that will satisfy all requirements defined by the complex Internet of Things systems.

Description: A modified multiobjective self-adaptive differential evolution algorithm (MMOSADE) is presented in this paper to improve the accuracy of multiobjective optimization design in the nuclear power system. The performance of the MMOSADE is tested by the ZDT test function set and compared with classical evolutionary algorithms. The results indicate that MMOSADE has a better performance in convergence and diversity. Based on the MMOSADE, a multiobjective optimization design platform for the nuclear power system is proposed, and the application of which is carried out. The evaluation program of the PRHR-HX in AP1000 is developed, and its reliability is verified. The optimal design schemes of PHHR-HX are obtained by utilizing the multiobjective optimization design platform. The results show that the optimal design schemes can envelop the prototype design scheme. This conclusion proves that the optimization design platform proposed in this paper is effective and feasible.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Internet of Things simulations play significant roles in the diverse kinds of activities in our daily lives and have been extensively researched. Creating and controlling virtual agents in three-dimensional Internet of Things simulations is a key technology for achieving realism in three-dimensional simulations. Given that traditional virtual agent-based approaches have limitations for realism, it is necessary to improve the realism of three-dimensional Internet of Things simulations. This article proposes a Q-Network-based motivation framework that applies a Q-Network to select motivations from desires and hierarchical task network planning to execute actions based on goals of the selected motivations. The desires are to be identified and calculated based on states. Selected motivations will be chosen to determine the goals that agents must achieve. In the experiments, the proposed framework achieved an average accuracy of up to 85.5% when the Q-Network-based motivation model was trained. To verify the Q-Network-based motivation framework, a traditional Q-learning is also applied in the three-dimensional virtual environment. Comparing the results of the two frameworks, the Q-Network-based motivation framework shows better results than those of traditional Q-learning, as the accuracy of the Q-Network-based motivation is higher by 15.58%. The proposed framework can be applied to the diverse kinds of Internet of Things systems such as a training autonomous vehicle. Moreover, the proposed framework can generate big data on animal behaviors for other training systems.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Cognitive radio–based vehicular ad hoc networks can solve the problem of limited spectrum resource and growing vehicular communication service demands in intelligent transportation systems, and thus, it receives much concern recently. In cognitive radio–based vehicular ad hoc networks, the high mobility of vehicles and the dynamic spectrum activity of cognitive radio make routing in such networks a great challenge. Some routing researches have been proposed in cognitive radio–based vehicular ad hoc networks with single-objective optimization and neglecting the nodes’ social behaviors which can improve the network performance. From this perspective, we propose a social-aware routing scheme for cognitive radio–based vehicular ad hoc networks, with the purpose of increasing the packet delivery ratio and decreasing the overhead ratio. First, we analyze the social centrality of primary users to offer an accuracy spectrum hole measurement. Moreover, we develop a social community partition algorithm to divide secondary users into intra-community and inter-community groups. Furthermore, considering the tradeoff between the packet delivery ratio and the overhead ratio, we adopt different replication policies and forwarding ranks in different community communication processes. In the intra-community communication process, we employ the single-copy policy and the contact duration rank. In the inter-community communication process, we utilize the optimized-binary-tree replication policy and the bridge coefficient rank. Simulation results show that our social-aware routing scheme achieves the higher package delivery ratio and the lower overhead ratio when compared with the existing cognitive radio–based vehicular ad hoc networks routing schemes and other standard routing schemes.

Description: COMSOL Multiphysics has been used to conduct thermal-hydraulic analysis in multiple nuclear applications. The aim of this study is to benchmark the prediction accuracy of COMSOL Multiphysics in performing thermal-hydraulic analysis of TRIGA (Training, Research, Isotopes, General Atomics) reactors such as the Geological Survey TRIGA Reactor (GSTR) by comparing its predictions with RELAP5 (a widely used code in nuclear thermal-hydraulic analysis) results and experimental data. The GSTR type is Mark I with a full thermal power of 1 MW, and it resides at the Denver Federal Center (DFC) in Colorado. The numerical investigation of the present work is carried out by developing single-subchannel thermal-hydraulic models of the GSTR utilizing RELAP5 and COMSOL codes. The models estimate the temperatures (fuel, outer clad, and coolant) and water flow patterns in the core as well as fuel element powers at which void starts to form within the coolant subchannels. Then, these models’ predictions are quantitatively evaluated and compared with the measured data.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉This article overviews the emerging use of deep neural networks in data analytics and explores which type of underlying hardware and architectural approach is best used in various deployment locations when implementing deep neural networks. The locations which are discussed are in the cloud, fog, and dew computing (dew computing is performed by end devices). Covered architectural approaches include multicore processors (central processing unit), manycore processors (graphics processing unit), field programmable gate arrays, and application-specific integrated circuits. The proposed classification in this article divides the existing solutions into 12 different categories, organized in two dimensions. The proposed classification allows a comparison of existing architectures, which are predominantly cloud-based, and anticipated future architectures, which are expected to be hybrid cloud-fog-dew architectures for applications in Internet of Things and Wireless Sensor Networks. Researchers interested in studying trade-offs among data processing bandwidth, data processing latency, and processing power consumption would benefit from the classification made in this article.

Description: A practical scale mechanical decladder that can slit spent nuclear fuel rod-cuts (hulls + pellets) of several tens of kg HM/batch is being developed to supply UO2 pellets to a voloxidation process. The mechanical decladder is an apparatus for separating and recovering fuel material and cladding tubes by horizontally slitting the cladding tube of a fuel rod and a defective irradiated fuel rod. In this study, we address the engineering design of the mechanical decladder for the pretesting of rod-cut slitting. To obtain the requirements of the mechanical decladder, we first manufactured a slitter for testing based on the decladding and shearing conditions of hulls and pellets. The performance test of the testing device for decladding was carried out using a 2-CUT blade module and a 3-CUT blade module. We evaluated the decladding methods for the mechanical decladder and selected the 3-CUT blade module based on the results. A buckling measurement instrument was used to perform a buckling verification test according to the length of a rod-cut and to determine decladder dimensions. The optimum decladding rod-cut length for buckling prevention was calculated. Furthermore, we analyzed the decladding mechanism for various slitting methods. Design/fabrication and preliminary tests of the practical scale mechanical decladder were also performed. For this purpose, we constructed the main mechanism by utilizing the SolidWorks modeling and analysis program and fabricated a new mechanical decladder. Based on the derived requirements, a mechanical decladder with three main modules was designed and fabricated for testing. Simulated rod-cuts of zircaloy were also manufactured to test the basic performance of the decladder, and a data acquisition system was constructed using RSC 232 to measure decladding force and velocity. In the basic test, the rod-cut was completely sectioned into three evenly spaced locations by the new mechanical decladder.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉Edge computing has recently emerged as an important paradigm to bring filtering, processing, and caching resources to the edge of networks. However, with the increasing popularity of augmented reality and virtual reality application, user requirements on data access speed have increased. Since the edge node has limited cache space, efficient data caching model is needed to improve the performance of edge computing. We propose a multi-objective optimization data caching model in the edge computing environment using data access counts, data access frequency, and data size as optimization goals. Our model differs from previous data caching schemes that focused only on data access counts or data size. In addition, a cyclic genetic ant algorithm is proposed to solve the multi-objective optimization data caching model. We compare the following three performance indicators: cache hit ratio, average response speed, and bandwidth cost. Simulation results show that the model can improve the cache hit ratio and reduce the response latency and the bandwidth cost.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: CIPS is a shift in the axial power towards the bottom half of the core, also known as axial offset anomaly (AOA), which results from the deposited of corrosion products during an operation. The main reason of CIPS is the solute particles especially boron compounds concentrated inside the porous deposit. The impact of CIPS is that the axial power distribution control may be more difficult and the shutdown margin can be decreased simultaneously. Besides, it also requires estimated critical condition (ECC) calculations to account for the effects of AOA. In this article, thermal-hydraulic subchannel code and boron deposit model have been combined to analyze the CIPS risk. The neutronics codes deal with the generation of homogenized neutron cross section as well as the calculation of local power factor. A simple rod assembly is analyzed with this combined method and simulation results are presented. Simulation results provide the boron hideout amount inside crud deposits and power shapes. The obtained results clearly show the power shape suppression in regions where crud deposits exist, which is a clear indication of CIPS phenomenon. And the CIPS effects on CHF have also been investigated. Result shows a margin of DNBR decrease in the crud case.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: After the severe accident (SA) occurred at the Three-Miles Island Nuclear Power Plant (NPP), important efforts on the investigation of the different phenomena during this kind of accidents have been started. Several experimental campaigns investigating one phenomenon at time or the combination of two or more phenomena have been performed. Today, the Phébus experimental campaign is probably the most important activity on the evaluation of the coupling among different phenomena. Four out of five tests investigated the degradation of an intact Pressurized Water Reactor (PWR) fuel bundle and the subsequent transport of Fission Products (FP) and Structural Materials (SM) through the primary circuit and into the containment, while the fifth test was only the degradation of a bed of PWR fuel bundle debris. These tests were performed between 1990 and 2010 at the CEA Cadarache laboratories (France) in a 5000:1 scaled facility. The main four tests varied the employed control rod materials, the fuel burn-up, and the oxidizing conditions of the atmosphere (strongly or weakly). The outcomes of this experimental campaign created a solid base for the understanding of the involved phenomena and allowed the development of models and software codes capable of simulating the evolution of a SA in a real NPP. ASTEC and MELCOR were two of the main SA codes profiting from the results of this Phébus campaign. These two codes were further improved in the latest years to account for the findings obtained in more recent experimental campaigns. A continuous verification and validation work is then necessary to check how the newer code’s versions reproduce the tests performed in these older experimental campaigns such as Phébus one. The present work is intended to be the final step of a series of publications covering the activities carried out at University of Pisa with the ASTEC and the MELCOR SA codes on the four Phébus tests employing an intact PWR fuel bundle. Because of the complexity and the extent of these tests, only the containment aspects were considered in the precedent works, i.e., only the thermal-hydraulics transient and its coupling with the FP and SM behavior. Then, general conclusions based on the outcomes of these precedent works are summarized in this work.

Description: For sequentially collected data, this paper introduces a lag-one differencing method to estimate the random error standard deviation and then uses the estimate to calculate a change detection threshold in a moving window method to detect shifts in the short-term systematic error. Performance results on simulated and real data are presented. Fortunately, the impact of having to perform change detection on the estimated short-term systematic and random error variances is anticipated to be modest or small. The motivating example arises from facilities under nuclear safeguards agreements, where inspector data collected during International Atomic Energy Agency (IAEA) verifications are compared to corresponding operator data. The differences between the operator and inspector values are evaluated using an application of analysis of variance (ANOVA). Typically, it is assumed that short-term systematic errors change across inspection periods, so inspection periods form the groups used in the ANOVA. In some data sets, it appears that the short-term errors have changed at other times, so change detection methods could be used to detect the actual change times.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉The study of the robust fatigue feature learning method for the driver’s operational behavior is of great significance for improving the performance of the real-time detection system for driver’s fatigue state. Aiming at how to extract more abstract and deep features in the driver’s direction operation data in the robust feature learning, this article constructs a fuzzy recurrent neural network model, which includes input layer, fuzzy layer, hidden layer, and output layer. The steering-wheel direction sensing time series sends the time series to the input layer through a fixed time window. After the fuzzification process, it is sent to the hidden layer to share the weight of the hidden layer, realize the memorization of the fatigue feature, and improve the feature depth capability of the steering wheel angle time sequence. The experimental results show that the proposed model achieves an average recognition rate of 87.30% in the fatigue sample database of real vehicle conditions, which indicates that the model has strong robustness to different subjects under real driving conditions. The model proposed in this article has important theoretical and engineering significance for studying the prediction of fatigue driving under real driving conditions.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉In mobile ad hoc networks, network nodes accomplish a target task usually by cooperative packet forwarding from the source to the destination. It is a challenge to enforce their mutual cooperation for a node’s self-interest. In this article, we focus on cooperative packet forwarding in a one-hop unreliable channel, which leads to packet loss and retransmission. We model the process of packet forwarding with the nodes’ remaining energy and reputation value. We propose a packet-forwarding non-cooperative game model reflecting the utilities of different packet-forwarding strategies, in which an incentive mechanism is introduced to enforce cooperation of packet forwarding. Furthermore, we analyze the packet-forwarding game with replicator dynamics and derive and prove three theorems. If the conditions of the theorems are met, the evolutionarily stable strategies can be attained. Three inferences also reveal how convergence speed to evolutionarily stable states is affected by the cooperative incentive, the probability of successful packet transmissions, and the upper limit of the retransmission number. The simulation results support the proposed theorems and inferences. In addition, we show that our game model with a reputation value and the mechanism of incentive cooperation can improve the probability of successful packet transmissions, and reduce the network overhead.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Recently, many lightweight block ciphers are proposed, such as PRESENT, SIMON, SPECK, Simeck, SPARX, GIFT, and CHAM. Most of these ciphers are designed with Addition–Rotation–Xor (ARX)-based structure for the resource-constrained environment because ARX operations can be implemented efficiently, especially in software. However, if the word size of a block cipher is smaller than the register size of the target device, it may process inefficiently in the aspect of memory usage. In this article, we present a fast implementation method for ARX-based block ciphers, named two-way operation. Moreover, also we applied SPARX-64/128 and CHAM-64/128 and estimated the performance in terms of execution time (cycles per byte) on a 32-bit Advanced RISC Machines processor. As a result, we achieved a large amount of improvement in execution time. The cycles of round function and key schedule are reduced by 53.31% and 31.51% for SPARX-64/128 and 41.22% and 19.40% for CHAM-64/128.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 11, November 2019. 〈br/〉Flying ad hoc network is widely used in many military and civilian scenarios. Compared with mobile ad hoc network and vehicular ad hoc network, flying ad hoc network holds some special characteristics such as high mobility, long-distance communication, and sparse node-deployment, which cause an important challenge in the design of routing protocols. In this article, a velocity-aware and stability-estimation–based multi-path routing protocol is proposed for flying ad hoc network. The protocol is mainly composed of two important parts, which are the routing discovery mechanism and routing maintenance mechanism. In routing discovery process, the routing discovery request packet only can be forwarded by the reliable node, which is decided by the calculation of co-direction degree, then the routing overhead is reduced at some extent. Noticeably, the correlation of the survival duration between adjacent links is fully considered, which is very important to the path stability criteria. In routing maintenance progress, a path similarity and path remaining survival duration–based multi-path selection mechanism is proposed. The performance superiority of velocity-aware and stability-estimation–based multi-path routing protocol is also demonstrated by extensive simulations. The results show that velocity-aware and stability-estimation–based multi-path routing protocol is much better than other existing protocols in terms of network throughput, average delay of data transmission, routing overhead, and the convergence time of the routing discovery.

Description: This study presents the time-dependent analyses of transmutations of long-lived fission products (LLFPs) and medium-lived fission products (MLFPs) occurring in thermal reactors in a conceptual helium gas-cooled accelerator-driven system (ADS). In accordance with this purpose, the CANDU-37 and PWR 15 × 15 spent fuels are separately considered. The ADS consists of LBE-spallation neutron target, subcritical fuel zone, and graphite reflector zone. While the considered ADS is fueled with the spent nuclear fuels extracted from each thermal reactor without the use of additional fuel, fission products extracted from same thermal reactor are also placed into transmutation zone in graphite reflector zone. The LLFP transmutation performance of the modified ADS is analyzed by considering three different spent fuels extracted from the thermal reactors. Spent fuels are extracted from CANDU-37 in case A, from PWR-15 × 15 in case B, and from CANDU-37 fueled with mixture of PWR 15 × 15 spent fuel and 46% ThO2 in case C. The LBE target is bombard with protons of 1000 MeV. The proton beam power is assumed as 20 MW, which corresponds to 1.24828·1017 protons per second. MCNPX 2.7 and CINDER 90 computer codes are used for the time-dependent burn calculations. The ADS is operated under subcritical mode until the value of keff increases to 0.984, and the maximum operation times are obtained as 3400, 3270, and 5040 days according to the spent fuel cases of A, B, and C, respectively. The calculations bring out that in the modified ADS, LLFPs and MLFPs, which are extracted from thermal reactors, can be transformed to stable isotopes in significant amounts along with energy production.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 10, October 2019. 〈br/〉Gait analysis is an invaluable tool in diagnosing and monitoring human health. Current techniques often rely on specialists or expensive gait measurement systems. There is a clear space in the field for a simple, inexpensive, quantitative way to measure various gait parameters. This study investigates if useful quantitative gait parameters can be extracted from floor acceleration measurements produced by the input of foot falls. A total of 17 participants walked along a 115-ft-long hallway while underfloor mounted accelerometers measured the vertical acceleration of the floor. Signal-energy-based algorithms detect the heel strike of each step during trials. From the detected footsteps, gait parameters such as the average stride length, the time between steps, and the step signal energy were calculated. In this study, a single accelerometer was shown to be enough to detect steps over a 115-ft corridor. Distributions for all gait parameters measured were generated for each participant, showing a normal distribution with low standard deviation. The success of gait analysis using underfloor accelerometers presents possibilities in the widespread adaptation of gait measurements. The ease of installation and operation offers an opportunity to gather long-term gait measurements. Such data will augment current gait diagnostic approaches by filling the gaps between specialist visits.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 10, October 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 10, October 2019. 〈br/〉Accurate prediction of the generation capacity of photovoltaic systems is fundamental to ensuring the stability of the grid and to performing scheduling arrangements correctly. In view of the temporal defect and the local minimum problem of back-propagation neural network, a forecasting method of power generation based on long short-term memory-back-propagation is proposed. On this basis, the traditional prediction data set is improved. According to the three traditional methods listed in this article, we propose a fourth method to improve the traditional photovoltaic power station short-term power generation prediction. Compared with the traditional method, the long short-term memory-back-propagation neural network based on the improved data set has a lower prediction error. At the same time, a horizontal comparison with the multiple linear regression and the support vector machine shows that the long short-term memory-back-propagation method has several advantages. Based on the long short-term memory-back-propagation neural network, the short-term forecasting method proposed in this article for generating capacity of photovoltaic power stations will provide a basis for dispatching plan and optimizing operation of power grid.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 10, October 2019. 〈br/〉This article addresses the problem related to the reliability of path after transmitting the given amount of data with the service-level agreement cooperation in the computer communication network. The links have associated with service performance factor parameter during the data transmission, and each node is associated with the requested service performance factor. In this article, first we have considered the single objective to minimize the transmission time of the quickest path problem. An algorithm for quickest path problem has been proposed for results, and furthermore, its time complexity has been shown. The problem has been extended with bi-objective optimization of the quickest path problem, which minimizes the transmission time and hybrid logarithmic reliability. An algorithm is proposed for getting the number of efficient solutions for the quickest path problem using label-correcting algorithm. The algorithms are implemented and tested on different standard benchmark network problems provided with the set of Pareto front of the results.

Description: Thermal reactors have been considered as interim solution for transmutation of minor actinides recycled from spent nuclear fuel. Various studies have been performed in recent decades to realize this possibility. This paper presents the neutronic feasibility study on transmutation of minor actinides as burnable poison in the VVER-1000 LEU (low enriched uranium) fuel assembly. The VVER-1000 LEU fuel assembly was modeled using the SRAC code system, and the SRAC calculation model was verified against the MCNP6 calculations and the available published benchmark data. Two models of minor actinide loading in the LEU fuel assembly have been investigated: homogeneous mixing in the UGD (Uranium-Gadolinium) pins and coating a thin layer to the UGD pins. The consequent negative reactivity insertion by minor actinides was compensated by reducing the gadolinium content and boron concentration. The reactivity of the LEU assembly versus burnup and the transmutation of minor actinide nuclides were examined in comparison with the reference case. The results demonstrate that transmutation of minor actinides as burnable poison in the VVER-1000 reactor is feasible as minor actinides could partially replace the functions of gadolinium and boric acid for excess reactivity control.

Description: As key equipment in nuclear power plant, the reactor power control system is adopted to strictly control and regulate the reactor power of a PWR (pressurized water reactor) in a nuclear power plant. A well-optimized predictive control algorithm based on SDMC (stepped dynamic matrix controller) is developed and introduced in this paper and applied to the power regulation of a reactor power model. In addition, the test and verification of this application is conducted by two different methods and devices: the virtual verification platform and the physical DCS (digital control system). The result of the verification suggests that the application of SDMC gains a better performance in the maximum dynamic deviation, adjustment time, overshoot, and so on.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉State-of-the-art progress in cloud computing encouraged the healthcare organizations to outsource the management of electronic health records to cloud service providers using hybrid cloud. A hybrid cloud is an infrastructure consisting of a private cloud (managed by the organization) and a public cloud (managed by the cloud service provider). The use of hybrid cloud enables electronic health records to be exchanged between medical institutions and supports multipurpose usage of electronic health records. Along with the benefits, cloud-based electronic health records also raise the problems of security and privacy specifically in terms of electronic health records access. A comprehensive and exploratory analysis of privacy-preserving solutions revealed that most current systems do not support fine-grained access control or consider additional factors such as privacy preservation and relationship semantics. In this article, we investigated the need of a privacy-aware fine-grained access control model for the hybrid cloud. We propose a privacy-aware relationship semantics–based XACML access control model that performs hybrid relationship and attribute-based access control using extensible access control markup language. The proposed approach supports fine-grained relation-based access control with state-of-the-art privacy mechanism named Anatomy for enhanced multipurpose electronic health records usage. The proposed (privacy-aware relationship semantics–based XACML access control model) model provides and maintains an efficient privacy versus utility trade-off. We formally verify the proposed model (privacy-aware relationship semantics–based XACML access control model) and implemented to check its effectiveness in terms of privacy-aware electronic health records access and multipurpose utilization. Experimental results show that in the proposed (privacy-aware relationship semantics–based XACML access control model) model, access policies based on relationships and electronic health records anonymization can perform well in terms of access policy response time and space storage.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉In this work, a new hybrid clustering routing protocol is proposed to prolong network life time through detecting holes and edges nodes. The detection process attempts to generate a connected graph without any isolated nodes or clusters that have no connection with the sink node. To this end, soft clustering/estimation maximization with graph metrics, PageRank, node degree, and local cluster coefficient, has been utilized. Holes and edges detection process is performed by the sink node to reduce energy consumption of wireless sensor network nodes. The clustering process is dynamic among sensor nodes. Hybrid clustering routing protocol–hole detection converts the network into a number of rings to overcome transmission distances. We compared hybrid clustering routing protocol–hole detection with four different protocols. The accuracy of detection reached 98%. Moreover, network life time has prolonged 10%. Finally, hybrid clustering routing protocol–hole detection has eliminated the disconnectivity in the network for more than 80% of network life time.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉With the continuous expansion of the market of device-free localization in smart cities, the requirements of device-free localization technology are becoming higher and higher. The large amount of high-dimensional data generated by the existing device-free localization technology will improve the positioning accuracy as well as increase the positioning time and complexity. The positions required from single target to multi-targets become a further increasing difficulty for device-free localization. In order to satisfy the practical localizing application in smart city, an efficient multi-target device-free localization method is proposed based on a sparse coding model. To accelerate the positioning as well as improve the localization accuracy, a sparse coding-based iterative shrinkage threshold algorithm (SC-IA) is proposed and a subspace sparse coding-based iterative shrinkage threshold algorithm (SSC-IA) is presented for different practical application requirements. Experiments with practical dataset are performed for single-target and multi-targets localization, respectively. Compared with three typical machine learning algorithms: deep learning based on auto encoder, K-nearest neighbor, and orthogonal matching pursuit, experimental results show that the proposed sparse coding-based iterative shrinkage threshold algorithm and subspace sparse coding-based iterative shrinkage threshold algorithm can achieve high localization accuracy and low time cost simultaneously, so as to be more practical and applicable for the development of smart city.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉Movie data has a prominent role in the exponential growth of multimedia data over the Internet, and its analysis has become a hot topic with computer vision. The initial step towards movie analysis is scene segmentation. In this article, we investigated this problem through a novel intelligent Convolutional Neural Network (CNN) based three folded framework. The first fold segments the input movie into shots, the second fold detects objects in the segmented shots and the third fold performs object-based shots matching for detecting scene boundaries. Texture and shape features are fused for shots segmentation, and each shot is represented by a set of detected objects acquired from a light-weight CNN model. Finally, we apply set theory with the sliding window–based approach to integrate the same shots to decide scene boundaries. The experimental evaluation indicates that our proposed approach outran the existing movie scene segmentation approaches.

Description: In this study, we first examined the sorption of Pd on MX-80 in Na-Ca-ClO4 solution as a function of (3–9) and ionic strength (0.1 M–4 M) and confirmed that the experimentally derived values could be fitted by a 2-site protolysis nonelectrostatic surface complexation and cation exchange (2SPNE SC/CE) model using three binary surface complexation constants previously estimated. Then, we investigated the sorption of Pd on MX-80 in Na-Ca-Cl-ClO4 solution as a function of (3–9) and molar concentration ratio (0–∞) at the ionic strength = 4 M. We found that the sorption of Pd on MX-80 in Na-Ca-Cl-ClO4 solution could be simulated only by the three binary and one ternary surface complexations (). This suggests that the contribution of other ternary surface complexations such as ≡S-OH ≡ ( = 1, 2 and 3) to Pd sorption in Na-Ca-Cl-ClO4 solution with ionic strength = 4 M was negligibly small.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉The success of the wilderness search and rescue missions is highly dependent on the time required to search for the lost person. The use of unmanned aerial systems may enhance search and rescue missions by supplying aerial support of the search process. There are unmanned aerial system–based solutions, which are capable of detecting the lost person using computer vision, infrared sensors, and detection of a mobile phone signal. The most pressing issue is reducing the cost of a search and rescue mission. Thus, to improve the efficiency of the resource utilization in wilderness search scenario, we consider the use of unmanned aerial system for both mobile phone detection and enabling Wi-Fi communication for the ground portion of the search and rescue team. Such an approach does not require specific additional tools (e.g. access point, specific user equipment) for communication, which reduces the cost and improves the scalability and coordination of the search and rescue mission. As a result, the article provides methods of searching the wilderness for a person using beacon signals from a mobile phone for two situations: when the distance to the source of emergency signals is unknown and when the distance is known. In addition, the voice transmission delay and the number of unmanned aircrafts are found to guaranty the quality of a call.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉We propose a robust and accurate camera pose determination method based on geometric optimization search using the Internet of Things (IoT). The central idea is to (1) obtain image information through Internet of Things technology, (2) obtain the first pose by minimizing the error function, and (3) use the geometric relationship and constraint condition to obtain the appropriate attitude angles as a new initial value for the next iteration calculation. The features of this method are as follows. First, this method can deal with a large amount of uncertain data, such as in the case of any shooting angle, in the case of any reference point, and in the case of a small number of feature points. Finally, because of using Internet of Things technology, our method can quickly complete data processing and transmission. Compared to state-of-the-art methods, the experimental results show that our approach performs well on both synthetic and real data and can be used to provide accurate and stable data for subsequent applications.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: To ensure that the outside dose rate of waste package is below the limitation of national laws and regulations, based on the standard 200L drum, a new drum with inner shielding was proposed for intermediate-level radioactive waste (ILW) storage. For comparison, FLUKA and QAD-CGA were used to verify the shielding design of the ILW storage drums produced in INET with multiple inner shielding layers. The flux and dose were calculated and analyzed for four different cases. In QAD-CGA calculation, it was found that different buildup factors can lead to the considerably different results. A weighted algorithm was proposed to correct QAD-CGA for multilayer shielding cases. In FLUKA calculation, parameter optimization and tailored variance reduction technique (VRT) were used. Quantitative efficiency evaluation of different FLUKA settings using the FOM factor was carried out. The differences in the calculated dose rates results between the FLUKA and QAD-CGA programs are within one order of magnitude. The results of QAD-CGA are generally higher than those of FLUKA. The analysis shows that appropriate corrections in QAD-CGA can make the trend of the calculation results more consistent with the theory. In FLUKA calculation, with optimized setting and VRT adopted, the calculation efficiency can be improved more than 20 times. The results of this study provide not only suggestions for the design of the ILW storage drums but also useful references for other similar work.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉A wireless body area network is a collection of Internet of Things–based wearable heterogeneous computing devices primarily used in healthcare monitoring applications. A lot of research is in process to reduce the cost and increase efficiency in medical industry. Low power sensor nodes are often attached to high-risk patients for real-time remote monitoring. These sensors have limited resources such as storage capacity, battery life, computational power, and channel bandwidth. The current work proposes a multi-hop Priority-based Congestion-avoidance Routing Protocol using IoT based heterogeneous sensors for energy efficiency in wireless body area networks. The objective is to devise a routing protocol among sensor nodes such that it has minimum delay and higher throughput for emergency packets using IoT based sensor nodes, optimal energy consumption for longer network lifetime, and efficient scarce resource utilization. In our proposed work, data traffic is categorized into normal and emergency or life-critical data. For normal data traffic, next-hop selection will be selected based upon three parameters; residual energy, congestion on forwarder node, and signal-to-noise ratio of the path between source and forwarder node. We use the data aggregation and filtration technique to reduce the network traffic load and energy consumption. A priority-based routing scheme is also proposed for life-critical data to have less delay and greater throughput in emergency situations. Performance of the proposed protocol is evaluated with two cutting-edge routing techniques iM-SIMPLE and Optimized Cost Effective and Energy Efficient Routing. The proposed model outperforms in terms of network throughput, traffic load, energy consumption, and lifespan.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 6, June 2019. 〈br/〉With the acceleration of the construction of smart city in China, the construction of a smart community that acts as the last mile of a smart city is highly valued. Development of smart community service integrated management platform is to utilize intelligent equipment and software platform, to build an information platform for information sharing, service integration, and resource optimization, and to ultimately realize intelligent management and innovative services within the community. In this article, we propose the overall framework and application system of the intelligent community integrated service platform, providing a strong theoretical basis for the construction of smart communities at this stage, and carry out detailed analysis and design of the underlying infrastructure, supporting platform and basic database of the platform.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 2, February 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 2, February 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 2, February 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 2, February 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 2, February 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 4, April 2019. 〈br/〉

Description: Reactor pressure vessel (RPV) support is a key safety facility which is categorized as Class 1 in the ASME nuclear safety design. The temperature distribution of RPV support is one of the key considerations for the concrete safety contacting with the bottom of the support. So it is necessary for accurate evaluation on the temperature field characteristics of RPV support, especially the bottom of support. This paper investigates the temperature field characteristics of modified RPV support which will be applied to a large advanced pressurized water reactor. A support entity is manufactured in a ratio of 1:1, and its temperature distribution is measured under simulated reactor operating conditions. Numerical simulation is also used to validate the results by the developed CFD model. The results show that under the operating conditions, of which the inlet cooling air temperature is 35.35°C and the velocity is 6.25 m/s, the temperature distribution of modified RPV support bottom is uneven, and the highest temperature is around 38°C, which is much lower than the demanding design temperature 93.3°C. Therefore, the design of the modified RPV support is reliable. In addition, the results of numerical simulation agree well with the experimental results with the error less than ±4°C, which ensures the reliability of the conclusion. The effects of inlet cooling air temperature and velocity on the RPV support temperature distribution are further studied. Both the temperature decrease and velocity increase can reduce the RPV support temperature. But the effect of inlet cooling air temperature is more obvious than inlet cooling air velocity. So the best way to improve air cooling capacity is to decrease the support inlet cooling air temperature. The results can provide a good guidance to the design of RPV support for the subsequent large advanced pressurized water reactor.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 3, March 2019. 〈br/〉

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Hybrid wireless mesh networks are suitable to construct emergency communication networks after disasters in underground mines. The routing decision in emergency scene is more difficult to give an accurate mathematical description due to the constraints of various data types, different data transmission requirements, and multi-parameters. Based on the fuzzy decision theory, this article has proposed a fuzzy-logic-based data-differentiated service supported routing protocol. Through the use of the adaptive fuzzy decision system, fuzzy-logic-based data-differentiated service supported routing protocol can provide data-differentiated services and make optimized routing decisions to satisfy the transmission requirements of different data types. In addition, a path soft handoff strategy has been proposed to maintain continuous data transmission when the path quality deteriorates. Based on NS2, we set three transmission scenarios (transmitting emergency data, regular data, or mixed data) to test the performances of fuzzy-logic-based data-differentiated service supported routing protocol, ad hoc on-demand distance vector, FUZZY-ad hoc on-demand distance vector, and multi-criteria routing metric. The results show that the fuzzy-logic-based data-differentiated service supported routing protocol has a higher delivery ratio and lower end-to-end delay when transmitting emergency data. When transmitting regular data, fuzzy-logic-based data-differentiated service supported routing protocol has achieved higher throughput and longer network lifetime than that of similar algorithms.

Description: For most of the remote maintenance activities of equipment in a hot cell, replacing breakdown modules is preferred over in situ repair because of insufficient space in the cell and the limited operability of remote handling tools. In such cases, the maintenance operation can be decomposed into transport of the new modules to the failed equipment, replacement of the broken modules with new ones, and then transport of the broken parts to the reserved space for further repair or disposal. In this respect, transfer is the most basic operation during remote maintenance, which is also true for the maintenance of pyroprocessing equipment. Hence, this paper proposes a maintenance automation framework for automated pyroprocessing equipment from the standpoint of module transfer. For the maintenance automation framework, maintenance-related functions and events are defined, and they are integrated with the pyroprocess automation framework. The proposed framework is verified by a case study on the maintenance of a large module through a hardware-in-the-loop simulation.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Location-based services has been widely applied in cloud-enabled Internet of vehicles. Within these services, location privacy issues have captured significant attention. Vehicles use the technology of anonymity to implement occultation, the location is not revealed. In this process, large-scale data transmissions can reduce the quality of services. In order to ensure location privacy and high-quality services, the cloud manager customizes virtual machines for vehicles to support location-based services according to the vehicles’ demands. To achieve better performance, this article presents a conditional anonymity method that does not use bilinear pairings to address the problem of privacy disclosure by using discrete logarithm problem and Diffie–Hellman problem. Moreover, asymmetric key algorithms are used in the Internet of vehicles environment to reduce the cost. To guarantee secure data transmission in Internet of vehicles, the batch validation technique is used to address data integrity. Our theoretical security analysis and experiments show that the proposed scheme is secure in compared attack models, such as impersonation attacks, replay attacks, the man-in-the-middle attacks, and so on. Our proposed scheme ensures the security requirements such as message authentication, location privacy protection, and traceability, while lowering transmission and computation cost.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉The existing privacy-preserving aggregation query processing methods in sensor networks rely on pre-established network topology and require all nodes in the network to participate in query processing. Maintaining the topology results in a large amount of energy overhead, and in many cases, the user is interested only in the aggregated query results of some areas in the network, and thus, the participation of the entire network node is not necessary. Aiming to solve this problem, this article proposes a spatial range aggregation query algorithm for a dynamic sensor network with privacy protection (energy-efficient privacy-preserving data aggregation). The algorithm does not rely on the pre-established topology but considers only the query area that the user is interested in, abandoning all nodes to participate in distributing the query messages while gathering the sensory data in the query range. To protect node data privacy, Shamir’s secret sharing technology is used to prevent internal attackers from stealing the sensitive data of the surrounding nodes. The analysis and experimental results show that the proposed algorithm outperforms the existing algorithms in terms of energy and privacy protection.