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Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features

Published: 11 June 2012 Publication History

Abstract

Wireless Sensor Networks (WSNs) have acquired new features recently, i.e., both the sensor and the antenna of a node can be directional. This brings new challenges to the Connected Coverage (CoCo) problem, where a finite set of targets needs to be monitored by some active sensor nodes, and the connectivity of these active nodes with the sink must be retained at the same time. In this paper, we study the Minimum-Energy Connected Coverage (MeCoCo) problem in WSNs with Omni-directional (O) and Directional (D) features, aiming at minimizing the total energy cost of both sensing and connectivity. Considering different combinations of O and D features, we study the MeCoCo problem under four cases, namely: O-Antenna and O-Sensor (OAOS), O-Antenna and D-Sensor (OADS), D-Antenna and D-Sensor (DADS), as well as D-Antenna and O-Sensor (DAOS). We prove that the MeCoCo problem is NP-hard under all these cases, and present approximation algorithms with provable approximation ratios. In particular, we propose a constant-approximation for OAOS, and polylogarithmic approximations for all other cases. Finally, we conduct extensive simulations and the results strongly confirm the effectiveness of our approach.

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    cover image ACM Conferences
    MobiHoc '12: Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing
    June 2012
    280 pages
    ISBN:9781450312813
    DOI:10.1145/2248371
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    Published: 11 June 2012

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    Author Tags

    1. connectivity
    2. coverage
    3. directional antenna
    4. directional sensor
    5. energy efficiency
    6. wireless sensor networks

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    • (2023)A novel model for representing a plane target and finding the worst-case coverage in wireless sensor network based on Clifford algebraEURASIP Journal on Wireless Communications and Networking10.1186/s13638-023-02301-z2023:1Online publication date: 19-Sep-2023
    • (2023)Target Coverage and Connectivity in Directional Wireless Sensor NetworksIEEE INFOCOM 2023 - IEEE Conference on Computer Communications10.1109/INFOCOM53939.2023.10229093(1-10)Online publication date: 17-May-2023
    • (2022)A Novel Framework for the Coverage Problem in Battery-Free Wireless Sensor NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2020.301947021:3(783-798)Online publication date: 1-Mar-2022
    • (2021)Joint Deployment Strategy of Battery-Free Sensor Networks with Coverage GuaranteeACM Transactions on Sensor Networks10.1145/345712317:4(1-29)Online publication date: 22-Jul-2021
    • (2020) Connected Target ϵ -probability Coverage in WSNs With Directional Probabilistic Sensors IEEE Systems Journal10.1109/JSYST.2019.293917814:3(3399-3409)Online publication date: Sep-2020
    • (2020)Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issuesThe Journal of Supercomputing10.1007/s11227-020-03166-5Online publication date: 20-Jan-2020
    • (2020)3D camera sensor scheduling algorithms for indoor multi-objective trackingJournal of Combinatorial Optimization10.1007/s10878-020-00532-0Online publication date: 28-Jan-2020
    • (2019)Broadcast Scheduling in Battery-Free Wireless Sensor NetworksACM Transactions on Sensor Networks10.1145/335647215:4(1-34)Online publication date: 27-Sep-2019
    • (2019)Dominating Sets Construction in RF-based Battery-free Sensor Networks with Full Coverage GuaranteeACM Transactions on Sensor Networks10.1145/335248615:4(1-29)Online publication date: 20-Sep-2019
    • (2019)BikeGPSACM Transactions on Sensor Networks10.1145/334385715:4(1-28)Online publication date: 17-Oct-2019
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