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首页> 外文期刊>Ad-hoc & sensor wireless networks >A Two-stage Clustering Sleep Scheduling Algorithm with Particle Swarm Optimization in Wireless Sensor Networks
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A Two-stage Clustering Sleep Scheduling Algorithm with Particle Swarm Optimization in Wireless Sensor Networks

机译:无线传感器网络中具有粒子群算法的两阶段聚类睡眠调度算法

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摘要

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.
机译:无线传感器网络(WSN)中传感器节点的能量是有限的,并且难以补充,因此,节能和能源管理在延长网络寿命方面起着非常重要的作用。为了提高能源利用效率,提出了一种结合粒子群算法和睡眠调度算法的两阶段粒子群优化睡眠调度算法(TCSS-PSO)。在两个阶段采用不同的睡眠调度机制:集中式睡眠调度机制和分布式睡眠调度机制。在集中式睡眠调度机制中,粒子群优化(PSO)用于平衡网络覆盖范围和能耗。分布式睡眠调度机制根据节点的邻居信息和剩余能量对节点进行调度,同时提供自动唤醒机制以确保网络覆盖并有效响应网络变化。分析和仿真结果表明,该算法可以在提高网络能耗有效性和保持网络覆盖范围之间取得良好的平衡,在一定程度上有效地延长了网络的寿命。

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