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Optimal Model for Energy-Efficient Clustering in Wireless Sensor Networks Using Global Simulated Annealing Genetic Algorithm

机译:无线传感器网络中使用全局模拟退火遗传算法的节能集群优化模型

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Since the operations of sensors in wireless sensor networks (WSNs) mainly rely on battery energy, energy consumption becomes an important issue. In this paper, we use a global simulated annealing genetic algorithm (GSAGA) to create energy efficient clusters for routing in WSNs. The simulation results show that the proposed GSAGA algorithm has higher efficiency and can achieve better network lifetime and data delivery at the base station than a few existing cluster-based routing protocols.
机译:由于无线传感器网络(WSNS)中传感器的操作主要依赖于电池能量,因此能量消耗成为一个重要问题。在本文中,我们使用全局模拟退火遗传算法(GSAGA)来创建用于在WSN中路由的节能群集。仿真结果表明,所提出的GSAGA算法具有更高的效率,并且可以在基站上实现更好的网络生存时间和数据传送,而不是一些基于群集的路由协议。

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