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Context-Aware Routing Algorithm for WSNs Based on Unequal Clustering

机译:基于不等群集的WSN的上下文感知路由算法

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Clustering and multi-hop routing algorithms prolongs the lifetime of wireless sensor networks(WSNS) substantially. However, existing algorithms usually consider clustering and routing as two independent problems. Information exchanged in clustering phase is not fully utilized in routing phase. Energy Hole is another problem that shrinks the lifetime of WSNs due to the characteristics of the multi-hop forwarding model. In this paper, we propose a Context-Aware Unequal-Clustering Routing Algorithm (CAUCR) for WSNs, which consists of an Optimized Weighted Unequal-Clustering Algorithm (OWUCA) and a Reverse Minimum Energy (RME) multi-hop routing algorithm. During our OWUCA clustering process, we additionally save some useful information for the subsequent RME routing algorithm, including minimum energy, minimum hop to base, and residual energy of neighbor cluster heads. RME starts routing construction based on the cluster head's distance to the sink, and the cluster head closer to the sink forms the routing table earlier. At the same time, RME utilizes the saved clustering information to reduce the overhead and energy consumption of the routing phase. Simulation results show that our CAUCR balances the energy consumption among sensor nodes, relieves the influence of "energy hole", and achieves an obvious improvement on the network lifetime.
机译:聚类和多跳路由算法基本上延长了无线传感器网络(WSNS)的寿命。但是,现有算法通常会考虑聚类和路由作为两个独立问题。在路由阶段不充分利用在聚类阶段交换的信息。能量孔是由于多跳转发模型的特征导致WSN的寿命缩小的另一个问题。在本文中,我们提出了一种关于WSN的上下文知识的不等聚类路由算法(CAUCR),其包括优化的加权不等群集算法(OWUCA)和反向最小能量(RME)多跳路由算法。在我们的OWUCA聚类过程中,我们还为后续RME路由算法保存了一些有用的信息,包括最小能量,最小跳跃以及邻居群集头的剩余能量。 RME根据簇头的距离开始路由结构,并且较近接收器的簇头更早地形成路由表。同时,RME利用保存的群集信息来减少路由阶段的开销和能量消耗。仿真结果表明,我们的CAUCR平衡了传感器节点之间的能量消耗,减轻了“能量孔”的影响,并实现了网络寿命的明显改进。

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