WSN Coverage Enhancement Algorithm Based on Particle Swarm Optimization

Abstract:

For the optimization of WSN coverage, this paper proposes a coverage optimization approach: Adaptive Disturbance Chaotic Particle Swarm Optimization, referred as ADCPSO. Based on the effective coverage of the network as the optimization goal, the method first conducts adaptive operation on the particles. Introducing perturbations factor and making particles trapped into local optimum quickly jump out, this method then use the randomness and the ergodicity of chaotic motion, to make local fine search. This effectively avoids particles’ “being premature” and improves the accuracy of the algorithm. The simulation results show that the ADCPSO algorithm can get better coverage.

• Periodical: Advanced Materials Research (Volumes 945-949)
• Pages: 2386-2393
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.945-949.2386
• Online since: June 2014
• Authors: Jian Xia Wang*, Xiang Li
• Keywords: Adaptive Disturbance Chaos, Coverage, Particle Swarm Optimization (PSO), Wireless Sensor Network (WSN)

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