A Particle Swarm Optimization Approach with Time-Varying Acceleration Coefficient for Hierarchical Clustering of Energy Efficiency Architecture in Wireless Sensor Networks

• Published in: Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 2696 - 2700
• Main Authors: Chen, Young-Long, Chen, Wan-Ren, Xiao, Gun-Wen, Ciou, Jing-Fong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2019
• Subjects: Base stations; cluster head; Clustering algorithms; Energy consumption; Energy efficiency; Hierarchical; Particle swarm optimization; PSO; Routing; sub-cluster head; Wireless sensor networks
• ISSN: 2577-1655
• DOI: 10.1109/SMC.2019.8914576

In this paper, we propose the hierarchical clustering of energy efficiency with particle swarm optimization (HCEE-PSO) algorithm for three-layer cluster architecture, divided into cluster and sub-cluster phases. We propose the total routing cost (TRC) to balance the energy of the sensor node, the sub-cluster head and the cluster head. In the sub-cluster head selection phase, we use the PSO algorithm to search for the suitable sub-cluster head. The cost function of the PSO algorithm ensures that the distance between the sub-cluster head and cluster head is not too close and that the amount of sub-cluster head energy is close to the cluster head energy. The entire wireless sensor networks (WSNs) is divided into three phases of transmission to save battery energy consumption of the cluster members and disperse the energy consumption of the cluster head. Simulation results show that our proposed HCEE-PSO algorithm reduces the energy consumption of WSNs and so extends their lifetime more than do LEACH architecture, the EECS algorithm or the MOECS algorithm.