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Energy EC : An artificial bee colony optimization based energy efficient cluster leader selection for wireless sensor networks

机译:能源EC:基于人工蜂殖民地优化的无线传感器网络的节能集群选择选择

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摘要

In recent times, the applications of cluster-based Wireless Sensor Networks (WSNs) have shown rapid growth. Many researchers are working on approaches for an efficient way of cluster formation and selecting a cluster leader in a way to improve the energy efficiency of the WSN. One of the biggest challenges for the selection of a suitable cluster leader is that which criteria should be given priority over others. This paper consists of such an approach that deals with the cluster leader selection in the cluster based on the fitness function. At first, the cluster of sensor nodes is created using the k-means clustering algorithm and then the optimization of the fitness function is done with nature-inspired optimization technique is known as Artificial Bees Colony (ABC) optimization. The objective function considered for the optimization is based on; sensor's energy; sink distance from cluster leader; and the cluster members distance. The benefit of the chosen objective function is that it yields the optimal cluster leaders. After simulating it is observed that the results obtained are better than that of other similar works.
机译:最近,基于集群的无线传感器网络(WSN)的应用已经显示出快速增长。许多研究人员正在努力实现群集形成的有效方式,并以提高WSN的能效的方式选择集群领导者。选择合适的集群领导者的最大挑战之一是,应该优先于他人的标准。本文包括这种方法,该方法根据适合函数涉及集群中的集群领导者选择。首先,使用K-Means聚类算法创建传感器节点群集,然后通过自然启发的优化技术进行健身功能的优化被称为人为蜜蜂殖民地(ABC)优化。考虑优化的目标函数是基于的;传感器的能量;距离集群负责人的距离;和集群成员距离。所选客观函数的好处是它产生最佳集群领导者。在模拟后,观察到所获得的结果优于其他类似作品的结果。

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