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An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs

机译:WSN的高效节能基于移动接收器的不平等群集机制

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摘要

Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network. In fact, the clustering technique will be considered effective if the energy consumed by sensor nodes decreases after applying clustering, however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this paper, the energy consumption of nodes, before clustering, is considered to determine the optimal cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent problem which leads to a remarkable decrease in the network’s lifespan. This problem stems from the asynchronous energy depletion of nodes located in different layers of the network. For this reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies could largely increase the network’s lifetime by decreasing the energy consumption of sensors and balancing the energy consumption among CHs.
机译:网络寿命和能效是用于评估无线传感器网络(WSN)的关键性能指标。减少和平衡节点的能耗可以用来延长网络寿命。在基于群集的WSN中,应用群集的目的之一是减少网络的能耗。实际上,如果在应用聚类后传感器节点消耗的能量减少,则聚类技术将被视为有效,但是,如果未正确选择聚类大小,则无法实现此目标。因此,在本文中,考虑在群集之前节点的能耗以确定最佳群集大小。采用两阶段遗传算法(GA)来确定群集大小的最佳间隔,并从该间隔中得出确切的值。此外,能量孔是一个固有的问题,会导致网络寿命的显着减少。此问题源于位于网络不同层中的节点的异步能量消耗。因此,我们提出了采用变化速度算法的移动水槽圆周运动(CM2SV2),以平衡簇头(CH)的能耗比。根据结果​​,这些策略可以通过减少传感器的能耗并平衡CH之间的能耗来大大延长网络的使用寿命。

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