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Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games

Chaofan Duan1, Jing Feng1,*, Haotian Chang1, Jianping Pan2, Liming Duan1

College of Meteorology and Oceanography, National University of Defense Technology, Nanjing, 211101, China.
Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8P 5C2, Canada.
Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia.

* Corresponding Author: Jing Feng. Email: email.

Computers, Materials & Continua 2019, 60(3), 989-1002. https://doi.org/10.32604/cmc.2019.06033

Abstract

Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which Nash Equilibrium exists. The proposed algorithm focuses on the local information of the neighboring sensors and decides sensors’ next action based on the actions of the other sensors, which maximizes its own utility function. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate that the proposed algorithm can enlarge the coverage of the entire monitoring area while achieving effective coverage of the events.

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Cite This Article

C. Duan, J. Feng, H. Chang, J. Pan and L. Duan, "Research on sensor network coverage enhancement based on non-cooperative games," Computers, Materials & Continua, vol. 60, no.3, pp. 989–1002, 2019. https://doi.org/10.32604/cmc.2019.06033

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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