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

Abstract

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.