Title: An adaptive clustering algorithm based on improved particle swarm optimisation in wireless sensor networks

Authors: Deng-ao Li; Hailong Hao; Guolong Ji; Jumin Zhao

Addresses: College of Information Engineering, Taiyuan University of Technology, 79 West Yingze Street, Taiyuan, 030024, Shanxi Province, China ' College of Information Engineering, Taiyuan University of Technology, 79 West Yingze Street, Taiyuan, 030024, Shanxi Province, China ' State Grid Shanxi Electric Power Research Institute, 6 Qingnian Road, Taiyuan, 030001, Shanxi Province, China ' College of Information Engineering, Taiyuan University of Technology, 79 West Yingze Street, Taiyuan, 030024, Shanxi Province, China

Abstract: In wireless sensor networks (WSNs), the lifetime of networks is a critical issue. In order to expand the lifespan of WSNs, an efficient technique is need to reduce energy consumption of WSNs. In this paper, an improved nonlinear dynamic adaptive particle swarm optimisation (NDAPSO) is applied for producing energy-aware clusters with selection of optimal cluster heads. The fitness function used for evaluating the particles consider four features, such as energy consumption, intra-cluster distance, the proportion of cluster heads energy and degree of energy consumption equilibrium. And a new cluster head competition mechanism is introduced in this paper. Then in the process of NDAPSO, the optimal cluster heads are selected by comparing quality of particles, which is evaluated by the fitness function. The simulation results show that this algorithm effectively reduces the communication energy consumption and improves the networks lifespan.

Keywords: wireless sensor networks; WSNs; network lifespan; particle swarm optimisation; nonlinear PSO; dynamic PSO; adaptive PSO; energy-aware clusters; cluster heads; proportion; energy consumption equilibrium; competition mechanism; evaluation; fitness function; adaptive clustering; intra-cluster distance; simulation.

DOI: 10.1504/IJHPCN.2015.072788

International Journal of High Performance Computing and Networking, 2015 Vol.8 No.4, pp.370 - 380

Available online: 27 Oct 2015 *

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