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A Balanced Power Consumption Algorithm Based on Enhanced Parallel Cat Swarm Optimization for Wireless Sensor Network

机译:基于增强并行Cat群算法的无线传感器网络均衡功耗算法

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The wireless sensor network (WSN) is composed of a set of sensor nodes. It is deemed suitable for deploying with large-scale in the environment for variety of applications. Recent advances in WSN have led to many new protocols specifically for reducing the power consumption of sensor nodes. A new scheme for predetermining the optimized routing path is proposed based on the enhanced parallel cat swarm optimization (EPCSO) in this paper. This is the first leading precedent that the EPCSO is employed to provide the routing scheme for the WSN. The experimental result indicates that the EPCSO is capable of generating a set of the predetermined paths and of smelting the balanced path for every sensor node to forward the interested packages. In addition, a scheme for deploying the sensor nodes based on their payload and the distance to the sink node is presented to extend the life cycle of the WSN. A simulation is given and the results obtained by the EPCSO are compared with the AODV, the LD method based on ACO, and the LD method based on CSO. The simulation results indicate that our proposed method reduces more than 35% power consumption on average.
机译:无线传感器网络(WSN)由一组传感器节点组成。它被认为适合在各种应用程序环境中进行大规模部署。 WSN的最新进展导致了许多新协议,专门用于减少传感器节点的功耗。本文提出了一种基于增强型并行猫群优化(EPCSO)的最优路由路径预定方案。这是使用EPCSO为​​WSN提供路由方案的第一个先例。实验结果表明,EPCSO能够生成一组预定路径,并能够为每个传感器节点熔化平衡路径以转发感兴趣的包裹。另外,提出了用于基于传感器节点的有效载荷和到宿节点的距离来部署传感器节点的方案,以延长WSN的生命周期。进行了仿真,并将EPCSO获得的结果与AODV,基于ACO的LD方法和基于CSO的LD方法进行了比较。仿真结果表明,我们提出的方法平均降低了35%以上的功耗。

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