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Trade-offs between mobility and density for coverage in wireless sensor networks

Published: 09 September 2007 Publication History
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  • Abstract

    In this paper, we study the coverage problem for hybrid networks which comprise both static and mobile sensors. We consider mobile sensors with limited mobility, i.e., they can move only once over a short distance. Such mobiles are simple and cheap compared to sophisticated mobile robots. In conventional static sensor networks, for a random deployment, the sensor density should increase as O(log L + k log log L) to provide k-coverage in a network with a size of L. As an alternative, an all mobile sensor network can provide k-coverage over the field with a constant density of O(k), independent of network size L. We show that the maximum distance that any mobile sensor will have to move is O(1 over √k log 3 over 4 (kL)). We then propose a hybrid network structure, comprising static sensors and a small fraction of O(1 over √(k)) of mobile sensors. For this network structure, we prove that k-coverage is achievable with a constant sensor density of O(k), independent of network size L. Furthermore, for this hybrid structure, we prove that the maximum distance which any mobile sensor has to move is bounded as O(log3 over 4 L). We then propose a distributed relocation algorithm, where each mobile sensor only requires local information in order to optimally relocate itself and characterize the algorithm's computational complexity and message overhead. Finally, we verify our analysis via extensive numerical evaluations.

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    1. Trade-offs between mobility and density for coverage in wireless sensor networks

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        cover image ACM Conferences
        MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking
        September 2007
        370 pages
        ISBN:9781595936813
        DOI:10.1145/1287853
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Published: 09 September 2007

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        Author Tags

        1. coverage
        2. mobility
        3. sensor networks

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        • (2021)A systematic literature review on mobility in terrestrial and underwater wireless sensor networksInternational Journal of Communication Systems10.1002/dac.479934:10Online publication date: 20-Apr-2021
        • (2019)Online hole healing for sensor coverageJournal of Global Optimization10.1007/s10898-019-00827-5Online publication date: 7-Sep-2019
        • (2018)Modeling and simulation of the optimal sink moving path based on mixed integer linear programmingJournal of Intelligent & Fuzzy Systems10.3233/JIFS-16937734:2(839-848)Online publication date: 27-Feb-2018
        • (2018)A Cooperative Spectrum Sensing Strategy for Dynamic Cognitive Radio Sensor Networks2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA)10.1109/ICA-ACCA.2018.8609855(1-6)Online publication date: Oct-2018
        • (2018)Coverage and Connectivity in WSNs: A Survey, Research Issues and ChallengesIEEE Access10.1109/ACCESS.2018.28336326(26971-26992)Online publication date: 2018
        • (2018)Approximating Sweep Coverage DelayUbiquitous Networking10.1007/978-3-030-02849-7_2(14-27)Online publication date: 3-Nov-2018
        • (2017)Optimal Routing for Lifetime Maximization of Wireless-Sensor Networks With a Mobile Source NodeIEEE Transactions on Control of Network Systems10.1109/TCNS.2016.25590184:4(793-804)Online publication date: Dec-2017
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