Group Head Selection in WSN using EM Algorithm

Tanuj Wala, N. Chand, A. Sharma
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Abstract

Recently wireless sensor network has become attractive field of research. A wireless sensor network (WSN) contains plenty of sensor nodes (SNs) that continuously monitor the physical phenomenon. The sensed data is cooperatively transferred through the network towards sink. In large wireless sensor network numerous nodes are deployed together to perform a task. The nodes have sensing, computing and communication features. Since the nodes are constrained in power, storage and computation, so it is necessary to deal with these issues efficiently. Therefore, a greater challenge is involved in saving energy and enhancing the lifespan of the network. Connectivity among the sensor nodes is another critical challenge in WSN due to limited communication range of sensor nodes. As a result, there arises the problem of network disconnection and huge energy consumption. The issues have been addressed in this paper and the proposal contains two phase scheme. In first phase, SGP (Spectral Graph Partitioning) technique is applied for the identification of disconnected portion of the network. Second phase is based on the improved EM (Expectation Maximization) clustering scheme for efficient cluster head and group head selection to diminish the energy consumption in the network.
基于EM算法的WSN组头选择
近年来,无线传感器网络已成为一个有吸引力的研究领域。无线传感器网络(WSN)包含大量的传感器节点(SNs),这些传感器节点持续监测物理现象。感知到的数据通过网络协同传输到sink。在大型无线传感器网络中,许多节点被部署在一起执行任务。节点具有传感、计算和通信功能。由于节点在功率、存储和计算方面受到限制,因此必须有效地处理这些问题。因此,节能和延长网络寿命是一个更大的挑战。由于传感器节点之间的通信范围有限,传感器节点之间的连接是WSN的另一个关键挑战。这就产生了断网问题和巨大的能源消耗。本文对这些问题进行了讨论,提出了两阶段方案。在第一阶段,采用谱图划分(SGP)技术对网络的断开部分进行识别。第二阶段是基于改进的EM(期望最大化)聚类方案进行高效的簇头和群头选择,以降低网络能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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