Dual Cluster Head Optimization of Wireless Sensor Networks Based on Multi-Objective Particle Swarm Optimization

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Abstract
Energy conservation is one of the main problems in a wireless sensor network (WSN). Compared with a single cluster head (CH), a dual CH optimization was proposed for less energy consumption by the WSN and an acquisition delay by the mobile sink (MS). Firstly, a fuzzy c-means clustering algorithm and a multi-objective particle swarm optimization were utilized for the determinations of the first and second CHs. Following that, the ideal trajectory of MS was assessed using the improved ant colony algorithm. Finally, the lifetimes, the death rounds of the first node and the 50% node, and the number of packets received at the base station were compared among the proposed approach. Moreover, five algorithms were compared to validate the optimization, and the improved trajectory was compared with the original one as well. It was found that, for 100 nodes, the number of dead rounds from the proposal increased by 7.9%, 22.9%, 25.1%, 61%, and 74.4% for the first node, and that of the 50% nodes increased by 27.8%, 34.2%, 98.3%, 213.1%, and 211.2%, respectively. The base station packet reception increased by about 19.3%, 53.5%, 27%, 86.8%, and 181.2%, respectively. The trajectory of MS could also decrease by about 10%.
Funding Information
  • S&T Program of Hebei (22282203Z)
  • Natural Science Foundation of Hebei Province (E2022209086, E2019209314)
  • National Natural Science Foundation of China (52004096)
  • Hebei Provincial Postdoctoral Science Foundation (B2020003033)
  • Research and Development Program of Science and Technology of Tangshan City 2019 (19130204g)
  • Basic Scientific Program of North China University of Science and Technology (JQN2022003)

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