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Energy-based clustering for wireless sensor network lifetime optimization

机译:基于能量的群集可优化无线传感器网络的寿命

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Clustering in wireless sensor networks is an efficient way to structure and organize the network. It aims to identify a subset of nodes within the network and bind it a leader (i.e. cluster-head). This latter becomes in charge of specific additional tasks like gathering data from all nodes in its cluster and sending them by using a longer range communication to a sink. As a consequence, a cluster-head exhausts its battery more quickly than regular nodes. In this paper, we present BLAC, a novel Battery-Level Aware Clustering family of schemes. BLAC considers the battery-level combined with another metric to elect the cluster-head. It comes in four variants. The cluster-head role is taken alternately by each node to balance energy consumption. Due to the local nature of the algorithms, keeping the network stable is easier. BLAC aims to maximize the time with all nodes alive to satisfy application requirements. Simulation results show that BLAC improves the full network lifetime 3-time more than traditional clustering schemes by balancing energy consumption over nodes and still delivering high data percentage.
机译:无线传感器网络中的群集是一种有效的网络结构和组织方式。它旨在识别网络中节点的子集,并将其绑定为领导者(即簇头)。后者负责特定的其他任务,例如从群集中所有节点收集数据,并通过与接收器的更远距离通信将其发送出去。结果,簇头比常规节点更快地耗尽其电池。在本文中,我们介绍了BLAC,这是一种新颖的电池级感知集群方案。 BLAC认为电池电量与另一个度量标准相结合以选出簇头。它有四个变体。每个节点交替使用群集头角色来平衡能耗。由于算法的本地性质,使网络保持稳定更加容易。 BLAC的目标是在所有节点都处于活动状态时最大化时间,以满足应用程序需求。仿真结果表明,BLAC通过平衡节点上的能耗并仍然提供高数据百分比,比传统群集方案将整个网络寿命提高了三倍。

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