基于能量分布的无线传感器网络聚类解决方案遗传算法

Sunil R. Gupta, N. Bawane, S. Akojwar
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引用次数: 4

摘要

在无线传感器网络(WSN)中,许多研究者证明了聚类技术可以提高网络的寿命。但是在靠近sink或基站(BS)的节点上处理流量的负载增加,因为它必须将其他节点的流量与自己的流量一起携带到BS,并且消耗更多的能量,从而导致网络漏洞。节点间传输的能量是可控的,每个传感器都可以直接传输到基站,但距离最远的节点消耗的能量更多,死亡时间更早。在这里,我们开发了一种有效的聚类技术,其中簇头(CH)形成并应该将数据发送到BS,并且CH的角色在每次旋转中发生变化。基于能量分布确定能量源,并利用遗传算法优化能量源的选择过程。结果表明,该方法增加了稳定运行周期,并与概率算法和EC算法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Clustering Solution for Wireless Sensor Networks Based on Energy Distribution & Genetic Algorithm
In a wireless sensor network (WSN), many researchers proved that the clustering technique improves the longevity of the network. But the load of handling traffic increases on the nodes which are closer to the sink or the base station (BS), as it has to carry others traffic along with its own towards the BS and depletes more energy which causes network holes. The power transmitted by the nodes could be controllable and each sensor can transmit directly to the BS but the farthest nodes consume more power and die earlier. Here we develop an efficient clustering technique in which cluster heads (CH) are formed and are supposed to send the data to the BS and the role of CH is changed in each rotation. The finalization of the CH is based on the energy distribution and its selection procedure is optimized using genetic algorithm (GA). The results show that with this approach the stable operating period increases and is compared with probabilistic and EC algorithm.
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