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An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks

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Abstract

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations; simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.

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Authors and Affiliations

  1. Computer Engineering Department, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

    Jaber Pournazari, Mohammad Alaei & Fahimeh Yazdanpanah

  2. Computer Engineering Department, Faculty of Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

    Mohammad Alaei & Fahimeh Yazdanpanah

Authors
  1. Jaber Pournazari
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  2. Mohammad Alaei
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  3. Fahimeh Yazdanpanah
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Correspondence to Mohammad Alaei.

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Pournazari, J., Alaei, M. & Yazdanpanah, F. An Energy Efficient Autonomous Method for Coverage Optimization in Wireless Multimedia Sensor Networks. Wireless Pers Commun 99, 717–736 (2018). https://doi.org/10.1007/s11277-017-5142-y

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  • DOI: https://doi.org/10.1007/s11277-017-5142-y

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