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A Coherent Approach for Dynamic Cluster-Based Routing and Coverage Hole Detection and Recovery in Bi-layered WSN-IoT

机译:基于动态集群的路由和覆盖孔检测和Bi-Signed WSN-IOT中的覆盖孔检测和恢复的相干方法

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Wireless sensor network is widely used in various applications such as military surveillance, wildlife monitoring, industrial process monitoring. Coverage hole detection and recovery is a major problem in WSN. It causes energy holes and increases the number of dead nodes. In this paper, we propose a bi-layered WSN architecture for dynamic clustering based routing and coverage hole detection and recovery. Our proposed work has four steps cluster formation, cluster head (CH) selection, coverage hole detection, and recovery and routing. Clusters are formed by the K-means algorithm. CH is elected by Determined Weight (DW). This DW is calculated by residual energy, distance from cluster and center to the base station. Based on the weight CH is selected. When the size of the cluster which is nearer to the base station is large then we explore cluster maintenance (cluster splitting and merging) for effective clustering by Efficient Entropy Function. After cluster formation, we perform coverage hole detection and recovery for successful packet transmission. Coverage holes occur in different locations. In this paper, we detect the coverage hole in three locations: (1) within the cluster, (2).among the cluster, (3).edge of the network. We use the hole manager (HM) at four different locations, it uses fuzzy logic (energy, stability) to find which node can recover coverage hole. The best multi-hop route is selected for transmission by Multi-objective Emperor Penguin Optimization Algorithm (MO-EPO). We implement our proposed approach for Agriculture Applications in WSN assisted with IoT. Finally, we analyse the performance of our proposed approach with respect to following metrics: Energy consumption, Network lifetime, Number of alive nodes and Packet delivery ratio. Our simulation results are implemented on the NS3.26 simulator.
机译:无线传感器网络广泛应用于各种应用,如军事监测,野生动物监测,工业过程监测。覆盖孔检测和恢复是WSN中的一个主要问题。它导致能量孔并增加死区数。在本文中,我们提出了一种基于动态聚类的路由和覆盖空穴检测和恢复的双层WSN架构。我们所提出的工作有四个步骤集群形成,群集头(CH)选择,覆盖孔检测和恢复和路由。群集由K-Means算法形成。 CH由确定的重量(DW)选为CH。该DW通过剩余能量,从簇和中心到基站的距离计算。选择了重量CH。当较近基站的群集大小很大时,我们探索通过有效熵函数的有效聚类的群集维护(群集拆分和合并)。在群集形成之后,我们为成功的数据包传输执行覆盖孔检测和恢复。覆盖孔发生在不同的位置。在本文中,我们检测到三个位置的覆盖孔:(1)在群集中,(2)。群集群,(3)。网络的指ge。我们在四个不同位置使用孔管理器(HM),它使用模糊逻辑(能量,稳定性)来查找哪个节点可以恢复覆盖孔。选择了最佳的多跳路线以通过多目标皇帝企鹅优化算法(MO-EPO)进行传输。我们在WSN协助的WSN中实施了拟议的农业应用方法。最后,我们分析了我们提出的方法对以下度量的表现:能源消耗,网络生命周期,活力节点数量和分组传递比率。我们的仿真结果是在NS3.26模拟器上实现的。

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