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

Xudong Yang
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引用次数: 1

Abstract

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. 
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基于剩余能量感知的无线传感器网络数据聚类方法
为了延长无线传感器网络的生存时间,提出了一种迭代算法。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,在每个子集群中构建数据转发均衡树。定义了各非簇头节点的数据转发路径,确定了移动数据采集器的移动路径,以剩余能量作为网络优化的依据。最后对该方案进行了仿真,并对两种传统的数据采集算法进行了比较。实验结果表明,本实验设计的算法能够有效地平衡WSN各节点的能耗,与传统的数据采集算法相比,性能有较大提升。综上所述,该算法可以显著降低网络的能耗,提高网络的生存期。
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