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In-network data aggregation route strategy based on energy balance in WSNs

机译:无线传感器网络中基于能量平衡的网络内数据聚合路由策略

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摘要

In-network data aggregation in wireless sensor networks (WSNs) can reduce data redundancy in the process of data gathering and therefore decrease energy consumption. Since aggregation cost sometimes can not be neglected in some realistic applications, it is important how to construct an effective route strategy which optimizes not only communication cost but also aggregation cost. In addition, we further study how to adaptively adjust route structure to avoid some nodes' premature death. To solve the above problems, we introduce heuristic algorithms based on discrete particle swarm optimization (DPSO). And the notions of mutation and crossover operators in genetic algorithm are incorporated into the discrete procedure of PSO, which can not only keep the diversity of population, but also make offspring population maintain the preferable characteristics. Experimental results show that our algorithms can effectively reduce energy consumption and trade off energy consumption and network lifetime, compared with other tree routing algorithms.
机译:无线传感器网络(WSN)中的网络内数据聚合可以减少数据收集过程中的数据冗余,从而降低能耗。由于在某些实际应用中有时无法忽略聚合成本,因此重要的是如何构建一种不仅优化通信成本而且优化聚合成本的有效路由策略。此外,我们进一步研究了如何自适应地调整路由结构以避免某些节点过早死亡。为了解决上述问题,我们引入了基于离散粒子群优化算法的启发式算法。遗传算法中的变异和交叉算子的概念被引入到PSO的离散过程中,不仅可以保持种群的多样性,而且可以使后代种群保持较好的特征。实验结果表明,与其他树形路由算法相比,我们的算法可以有效降低能耗,并权衡能耗和网络寿命。

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