Energy-balanced Sleep Scheduling Based on Particle Swarm Optimization in Wireless Sensor Network

In order to conserve battery power in wireless sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, determining which of the sensor nodes should be put into the sleep state is non-trivial. In this paper, an Energy-balanced Sleep Scheduling scheme based on Particle Swarm Optimization (EBSS-PSO) in the context of cluster-based sensor networks is proposed. The scheme aims to balance the energy load of the sensing and communication tasks among all the nodes in the cluster while provide adequate sensing coverage area and reduce the overlapping area. Analytical and simulation results are presented to evaluate the proposed EBSS-PSO scheme. It is shown that the EBSS-PSO scheme can extends the cluster´s overall network lifetime and reduce the overlapping area effectively while maintaining a similar sensing coverage compared with three related sleep scheduling schemes, the Randomized Scheduling (RS) scheme, the Neighbor-based Scheduling (NS) scheme and the Energy-Neighbor-based Scheduling (ENS) scheme.