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Data Clustering Method in Wireless Sensor Networks Based on Residual Energy Perception

机译:基于剩余能量感知的无线传感器网络数据聚类方法

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To prolong the survival time of wireless sensor network, an iterative scheme was proposed. First of all, spectrum clustering algorithm iteratively segmented the network into clusters, and cluster head nodes in each sub cluster were determined depending on the size of residual energy of sensor nodes. Then, a data forwarding balance tree was constructed in each sub cluster. Data forwarding path of each non-cluster head node was defined, and the moving path of a mobile data collector was determined, which used the residual energy as the basis for the network optimization. Finally, this scheme was simulated, and two traditional data gathering algorithms were compared. The results showed that the algorithm designed in this experiment could effectively balance energy consumption among all WSN nodes and had great performance improvement compared with the traditional data collection algorithm. To sum up, this algorithm can significantly reduce the energy consumption of the network and improve the lifetime of the network.?
机译:为了延长无线传感器网络的生存时间,提出了一种迭代方案。首先,频谱聚类算法将网络迭代分割成簇,并根据传感器节点剩余能量的大小确定每个子簇中的簇头节点。然后,在每个子群集中构建一个数据转发平衡树。定义了每个非集群头节点的数据转发路径,并确定了移动数据收集器的移动路径,该移动数据收集器使用剩余能量作为网络优化的基础。最后,对该方案进行了仿真,并比较了两种传统的数据收集算法。结果表明,与传统的数据收集算法相比,本实验设计的算法可以有效地平衡所有WSN节点之间的能耗,并具有很大的性能提升。综上所述,该算法可以显着降低网络能耗,提高网络寿命。

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