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  • 1
    Publication Date: 2012-09-29
    Description:    This work introduces decentralized query processing techniques based on MIDAS, a novel distributed multidimensional index. In particular, MIDAS implements a distributed k-d tree, where leaves correspond to peers, and internal nodes dictate message routing. MIDAS requires that peers maintain little network information, and features mechanisms that support fault tolerance and load balancing. The proposed algorithms process point and range queries over the multidimensional indexed space in only O (log n ) hops in expectance, where n is the network size. For nearest neighbor queries, two processing alternatives are discussed. The first, termed eager processing, has low latency (expected value of O (log n ) hops) but may involve a large number of peers. The second, termed iterative processing, has higher latency (expected value of O (log 2 n ) hops) but involves far fewer peers. A detailed experimental evaluation demonstrates that our query processing techniques outperform existing methods for settings involving real spatial data as well as in the case of high dimensional synthetic data. Content Type Journal Article Pages 1-31 DOI 10.1007/s10707-012-0163-x Authors George Tsatsanifos, National Technical University of Athens, Athens, Greece Dimitris Sacharidis, Institute for the Management of Information Systems, R.C. “Athena”, Athens, Greece Timos Sellis, National Technical University of Athens, Athens, Greece Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
    Published by Springer
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  • 2
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    Springer
    Publication Date: 2012-10-04
    Description:    In this paper, we present a novel method for fast lossy or lossless compression and decompression of regular height fields. The method is suitable for SIMD parallel implementation and thus inherently suitable for modern GPU architectures. Lossy compression is achieved by approximating the height field with a set of quadratic Bezier surfaces. In addition, lossless compression is achieved by superimposing the residuals over the lossy approximation. We validated the method’s efficiency through a CUDA implementation of compression and decompression algorithms. The method allows independent decompression of individual data points, as well as progressive decompression. Even in the case of lossy decompression, the decompressed surface is inherently seamless. In comparison with the GPU-oriented state-of-the-art method, the proposed method, combined with a widely available lossless compression method (such as DEFLATE), achieves comparable compression ratios. The method’s efficiency slightly outperforms the state-of-the-art method for very high workloads and considerably for lower workloads. Content Type Journal Article Pages 1-27 DOI 10.1007/s10707-012-0171-x Authors Đorđe M. Đurđević, University of Belgrade - School of Electrical Engineering, Bulevar kralja Aleksandra 73, 11120 Belgrade, Serbia Igor I. Tartalja, University of Belgrade - School of Electrical Engineering, Bulevar kralja Aleksandra 73, 11120 Belgrade, Serbia Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
    Published by Springer
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  • 3
    Publication Date: 2012-04-14
    Description:    Contour lines are important for quantitatively displaying relief and identifying morphometric features on a map. Contour trees are often used to represent spatial relationships between contours and assist the user in analysing the terrain. However, automatic analysis from the contour tree is still limited as features identified on a map by sets of contours are not only characterised by local relationships between contours but also by relationships with other features at different levels of representation. In this paper, a new method based on adjacency and inclusion relationships between regions defined by sets of contours is presented. The method extracts terrain features and stores them in a feature tree providing a description of the landscape at multiple levels of detail. The method is applied to terrain analysis and generalisation of a contour map by selecting the most relevant features according to the purpose of the map. Experimental results are presented and discussed. Content Type Journal Article Pages 1-24 DOI 10.1007/s10707-012-0153-z Authors Eric Guilbert, Department of Land Surveying and GeoInformatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 4
    Publication Date: 2012-04-14
    Description:    This paper describes an approach to using evolutionary algorithms for reasoning about paths through network data. The paths investigated in the context of this research are functional paths wherein the characteristics (e.g., path length, morphology, location) of the path are integral to the objective purpose of the path. Using two datasets of combined surface and road networks, the research demonstrates how an evolutionary algorithm can be used to reason about functional paths. We present the algorithm approach, the parameters and fitness function that drive the functional aspects of the path, and an approach for using the algorithm to respond to dynamic changes in the search space. The results of the search process are presented in terms of the overall success based on the response of the search to variations in the environment and through the use of an occupancy grid characterizing the overall search process. The approach offers a great deal of flexibility over more conventional heuristic path finding approaches and offers additional perspective on dynamic network analysis. Content Type Journal Article Pages 1-33 DOI 10.1007/s10707-012-0155-x Authors William M. Spears, Swarmotics, LLC, Laramie, WY, USA Steven D. Prager, University of Wyoming, Laramie, WY, USA Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 5
    Publication Date: 2012-04-17
    Description:    Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D . For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs ( O (| D |) in the worst case). PIR, on the other hand, reduces this bound to , but at the expense of high processing and communication overhead. We propose hybrid, two-step approaches for private location-based queries which provide protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect against excessive disclosure of POI locations, we devise two cryptographic protocols that privately evaluate whether a point is enclosed inside a rectangular region or a convex polygon. We also introduce algorithms to efficiently support PIR on dynamic POI sub-sets. We provide solutions for both approximate and exact NN queries. In the approximate case, our method discloses O (1) POI, orders of magnitude fewer than CR- or PIR-based techniques. For the exact case, we obtain optimal disclosure of a single POI, although with slightly higher computational overhead. Experimental results show that the hybrid approaches are scalable in practice, and outperform the pure-PIR approach in terms of computational and communication overhead. Content Type Journal Article Pages 699-726 DOI 10.1007/s10707-010-0121-4 Authors Gabriel Ghinita, Purdue University, West Lafayette, IN 47907, USA Panos Kalnis, King Abdullah University of Science and Technology, Jeddah, Saudi Arabia Murat Kantarcioglu, University of Texas at Dallas, Richardson, TX 75080, USA Elisa Bertino, Purdue University, West Lafayette, IN 47907, USA Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 4
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
    Published by Springer
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  • 6
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    Springer
    Publication Date: 2012-04-17
    Description:    As more data-intensive applications emerge, advanced retrieval semantics, such as ranking and skylines, have attracted the attention of researchers. Geographic information systems are a good example of an application using a massive amount of spatial data. Our goal is to efficiently support exact and approximate skyline queries over massive spatial datasets. A spatial skyline query, consisting of multiple query points, retrieves data points that are not father than any other data points, from all query points. To achieve this goal, we present a simple and efficient algorithm that computes the correct results, also propose a fast approximation algorithm that returns a desirable subset of the skyline results. In addition, we propose a continuous query algorithm to trace changes of skyline points while a query point moves. To validate the effectiveness and efficiency of our algorithm, we provide an extensive empirical comparison between our algorithms and the best known spatial skyline algorithms from several perspectives. Content Type Journal Article Pages 665-697 DOI 10.1007/s10707-010-0119-y Authors Mu-Woong Lee, Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea Wanbin Son, Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea Hee-Kap Ahn, Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea Seung-won Hwang, Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 4
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 7
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    Springer
    Publication Date: 2012-04-17
    Description: Special section on spatial and temporal databases Content Type Journal Article Category Editorial Pages 663-664 DOI 10.1007/s10707-011-0139-2 Authors Nikos Mamoulis, Department of Computer Science, University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong Thomas Seidl, Department of Computer Science 9, RWTH Aachen University, 52056 Aachen, Germany Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 4
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 8
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    Springer
    Publication Date: 2012-04-17
    Description:    Recently, several techniques have been proposed to protect the user location privacy for location-based services in the Euclidean space. Applying these techniques directly to the road network environment would lead to privacy leakage and inefficient query processing. In this paper, we propose a new location anonymization algorithm that is designed specifically for the road network environment. Our algorithm relies on the commonly used concept of spatial cloaking, where a user location is cloaked into a set of connected road segments of a minimum total length including at least users. Our algorithm is “query-aware” as it takes into account the query execution cost at a database server and the query quality, i.e., the number of objects returned to users by the database server, during the location anonymization process. In particular, we develop a new cost function that balances between the query execution cost and the query quality. Then, we introduce two versions of our algorithm, namely, pure greedy and randomized greedy , that aim to minimize the developed cost function and satisfy the user specified privacy requirements. To accommodate intervals with a high workload, we introduce a shared execution paradigm that boosts the scalability of our location anonymization algorithm and the database server to support large numbers of queries received in a short time period. Extensive experimental results show that our algorithms are more efficient and scalable than the state-of-the-art technique, in terms of both query execution cost and query quality. The results also show that our algorithms have very strong resilience to two privacy attacks, namely, the replay attack and the center-of-cloaked-area attack . Content Type Journal Article Pages 571-607 DOI 10.1007/s10707-010-0117-0 Authors Chi-Yin Chow, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China Mohamed F. Mokbel, Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA Jie Bao, Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA Xuan Liu, IBM Thomas J. Watson Research Center, Hawthorne, NY 10532, USA Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 3
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 9
    Publication Date: 2012-04-17
    Description:    Network data models are frequently used as a mechanism to describe the connectivity between spatial features in GIS applications. Real-life network models are dynamic in nature since spatial features can be periodically modified to reflect changes in the real world objects that they model. Such updates may change the connectivity relations with the other features in the model. In order to perform analysis the connectivity must be reestablished. Existing editing frameworks are not suitable for a dynamic environment, since they require network connectivity to be reconstructed from scratch. Another requirement for GIS network models is to provide support for a multiuser environment, where users are simultaneously creating and updating large amounts of geographic information. The system must support edit sessions that typically span a number of days or weeks, the facility to undo or redo changes made to the data, and the ability to develop models and alternative application designs without affecting the published database. The row-locking mechanisms adopted by many DBMSs is prohibitively restrictive for many common workflows. To deal with long-lasting transactions, a solution based on versioning is thus preferrable. In this paper we provide a unified solution to the problems of dynamic editing and versioning of network models. We first propose an efficient algorithm that incrementally maintains connectivity within a dynamic network. Our solution is based on the notion of dirty areas and dirty objects (i.e., regions or elements containing edits that have not been reflected in the network connectivity index). The dirty areas and objects are identified and marked during the editing of the network feature data; they are then subsequently cleaned and connectivity is re-built. Furthermore, for improving performance, we propose a ‘hyperedge’ extension to the basic network model. A hyperedge drastically decreases the number of edge elements accessed during solve time on large networks; this in turn leads to faster solve operations. We show how our connectivity maintenance algorithms can support the hyperedge enhanced model. We then propose a new network model versioning scheme that utilizes the dirty areas/objects of the connectivity rebuild algorithm. Our scheme uses flexible reconciling rules that allow the definition of a resolving mechanism between conflicting edits according to user needs. Moreover, the utilization of dirty areas/objects minimizes the overhead of tracking the editing history. The unified editing and versioning solution has been implemented and tested within ESRI’s ArcGIS system. Content Type Journal Article Pages 769-803 DOI 10.1007/s10707-011-0126-7 Authors Petko Bakalov, Environmental Systems Research Institute, Redlands, CA 92373, USA Erik Hoel, Environmental Systems Research Institute, Redlands, CA 92373, USA Wee-Liang Heng, Environmental Systems Research Institute, Redlands, CA 92373, USA Sudhakar Menon, Environmental Systems Research Institute, Redlands, CA 92373, USA Vassilis J. Tsotras, University of California, Riverside, CA 92507, USA Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 4
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
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  • 10
    Publication Date: 2012-04-17
    Description:    Intelligent crime analysis allows for a greater understanding of the dynamics of unlawful activities, providing possible answers to where, when and why certain crimes are likely to happen. We propose to model density change among spatial regions using a density tracing based approach that enables reasoning about large areal aggregated crime datasets. We discover patterns among datasets by finding those crime and spatial features that exhibit similar spatial distributions by measuring the dissimilarity of their density traces. The proposed system incorporates both localized clusters (through the use of context sensitive weighting and clustering) and the global distribution trend. Experimental results validate and demonstrate the robustness of our approach. Content Type Journal Article Pages 49-74 DOI 10.1007/s10707-010-0116-1 Authors Peter Phillips, School of Business, Discipline of IT, James Cook University, Townsville, Australia Ickjai Lee, School of Business, Discipline of IT, James Cook University, Townsville, Australia Journal GeoInformatica Online ISSN 1573-7624 Print ISSN 1384-6175 Journal Volume Volume 15 Journal Issue Volume 15, Number 1
    Print ISSN: 1384-6175
    Electronic ISSN: 1573-7624
    Topics: Geography
    Published by Springer
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