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首页> 外文期刊>International Journal of Technology >Bio-inspired, Cluster-based Deterministic Node Deployment in Wireless Sensor Networks
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Bio-inspired, Cluster-based Deterministic Node Deployment in Wireless Sensor Networks

机译:在无线传感器网络中以生物为灵感的基于集群的确定性节点部署

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The low-cost Wireless Sensor Network (WSN) consists of small battery powered devices called sensors, with limited energy capacity. Once deployed, accessibility to any sensor node for maintenance and battery replacement is not feasible due to the spatial scattering of the nodes. This will lead to an unreliable, limited lifetime and a poor connectivity network. In this paper a novel bio-inspired cluster-based deployment algorithm is proposed for energy optimization of the WSN and ultimately to improve the network lifetime. In the cluster initialization phase, a single cluster is formed with a single cluster head at the center of the sensing terrain. The second phase is for optimum cluster formation surrounding the inner cluster, based on swarming bees and a piping technique. Each cluster member distributes its data to its corresponding cluster head and the cluster head communicates with the base station, which reduces the communication distance of each node. The simulation results show that, when compared with other clustering algorithms, the proposed algorithm can significantly reduce the number of clusters by 38% and improve the network lifetime by a factor of 1/4.
机译:低成本无线传感器网络(WSN)由称为传感器的小型电池供电设备组成,具有有限的能量容量。一旦部署,由于节点的空间分散,无法访问任何传感器节点以进行维护和更换电池。这将导致不可靠,有限的生命周期以及较差的连接网络。本文提出了一种新颖的,基于生物启发的基于集群的部署算法,用于无线传感器网络的能量优化,并最终改善了网络寿命。在群集初始化阶段,将在感测地形的中心形成一个具有单个群集头的单个群集。第二阶段是基于蜂群和管道技术,围绕内部星团形成最佳星团。每个群集成员将其数据分发到其相应的群集头,并且群集头与基站通信,这缩短了每个节点的通信距离。仿真结果表明,与其他聚类算法相比,该算法可以将聚类数量减少38%,网络寿命提高1/4倍。

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