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A Two-stage Clustering Sleep Scheduling Algorithm with Particle Swarm Optimization in Wireless Sensor Networks
Wenzhong Guo, Guolong Chen, Chaolong Yu, Jinshu Su and Zhanghui Liu

The energy of sensor nodes in wireless sensor networks (WSNs) is limited and difficult to be replenished, therefore energy conservation and energy management play a very important role in prolonging network lifetime. To improve energy efficiency, a two-stage clustering sleep scheduling algorithm with particle swarm optimization (TCSS-PSO), combining clustering algorithm and sleep scheduling algorithm, is proposed in this paper. Different sleep scheduling mechanisms are adopted in two stages: a centralized sleep scheduling mechanism and a distributed sleep scheduling mechanism. In the centralized sleep scheduling mechanism, particle swarm optimization (PSO) is used to balance network coverage and energy consumption. Distributed sleep scheduling mechanism schedules the nodes according to their neighbors’ information and their remaining energy, while it provides an automatic wake-up mechanism to ensure network coverage and effectively respond to changes in the network. Analysis and simulation results show that our algorithm can make a good balance between the improvement of network energy consumption effectiveness and the maintenance of network coverage, effectively prolonging the network’s lifetime in some extent.

Keyword: Wireless sensor networks, energy management, clustering, sleep scheduling, particle swarm optimization.

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