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

机译:无线传感器网络中基于粒子群算法的能量平衡睡眠调度

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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.
机译:为了节省无线传感器网络中的电池电量,可以将某些传感器节点置于睡眠状态,而将其他传感器节点保持活动状态以进行传感和通信任务。但是,确定应将哪个传感器节点置于睡眠状态并非易事。在基于簇的传感器网络环境下,提出了一种基于粒子群优化(EBSS-PSO)的能量平衡睡眠调度方案。该方案旨在在群集中所有节点之间平衡感测和通信任务的能量负荷,同时提供足够的感测覆盖范围并减少重叠区域。给出了分析和仿真结果,以评估提出的EBSS-PSO方案。结果表明,与三种相关的睡眠调度方案(随机调度(RS)方案,基于邻居的调度())相比,EBSS-PSO方案可以延长群集的整体网络寿命并有效减少重叠区域,同时保持相似的感测覆盖范围NS)方案和基于能量邻居的调度(ENS)方案。

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