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    On Event Detection and Localization in Acyclic Flow Networks

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    Type
    Article
    Authors
    Suresh, Mahima Agumbe
    Stoleru, Radu
    Zechman, Emily M.
    Shihada, Basem cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Networks Laboratory (NetLab)
    Date
    2013-05
    Permanent link to this record
    http://hdl.handle.net/10754/348541
    
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    Abstract
    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures have been proven costly and imprecise, particularly when dealing with large-scale distribution systems. In this article, to the best of our knowledge, for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. We propose the idea of using sensors that move along the edges of the network and detect events (i.e., attacks). To localize the events, sensors detect proximity to beacons, which are devices with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensors and beacons deployed) in a predetermined zone of interest, while ensuring a degree of coverage by sensors and a required accuracy in locating events using beacons. We propose algorithms for solving the aforementioned problem and demonstrate their effectiveness with results obtained from a realistic flow network simulator.
    Citation
    On Event Detection and Localization in Acyclic Flow Networks 2013, 43 (3):708 IEEE Transactions on Systems, Man, and Cybernetics: Systems
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    DOI
    10.1109/TSMCA.2012.2210411
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6425511
    ae974a485f413a2113503eed53cd6c53
    10.1109/TSMCA.2012.2210411
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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