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A novel multi-objective coverage optimization memetic algorithm for directional sensor networks

Author

Listed:
  • Aimin Wang
  • Yingnan Gao
  • Jing Wu
  • Geng Sun
  • Wenjuan Jia

Abstract

For the target problem of a directional wireless sensor network, the greedy algorithm can easily fall into the local optimal solution, whereas the genetic algorithm must forecast the lifetime of the upper bound of the network. We propose a novel multi-objective coverage optimization memetic algorithm that encodes the solutions as chromosomes and simulates the biological evolution process in search for a favourable solution to address the aforementioned problems. Experimental results show that the proposed algorithm can prolong the network lifetime more effectively than similar heuristic algorithms in other studies.

Suggested Citation

  • Aimin Wang & Yingnan Gao & Jing Wu & Geng Sun & Wenjuan Jia, 2016. "A novel multi-objective coverage optimization memetic algorithm for directional sensor networks," International Journal of Distributed Sensor Networks, , vol. 12(7), pages 15501477166, July.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:7:p:1550147716657923
    DOI: 10.1177/1550147716657923
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    References listed on IDEAS

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    1. Jing Ai & Alhussein A. Abouzeid, 2006. "Coverage by directional sensors in randomly deployed wireless sensor networks," Journal of Combinatorial Optimization, Springer, vol. 11(1), pages 21-41, February.
    2. Cerulli, R. & De Donato, R. & Raiconi, A., 2012. "Exact and heuristic methods to maximize network lifetime in wireless sensor networks with adjustable sensing ranges," European Journal of Operational Research, Elsevier, vol. 220(1), pages 58-66.
    3. Xiu Deng & Jiguo Yu & Dongxiao Yu & Congcong Chen, 2012. "Transforming Area Coverage to Target Coverage to Maintain Coverage and Connectivity for Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 8(10), pages 254318-2543, October.
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