FUCBR: Fuzzy‐based unequal clustering and bat‐based routing protocol for WSNs assisted IoT

Abstract

SummaryThe internet of things (IoT) has recently become extremely important in our lives. With the advancement in IoT, wireless sensor networks (WSNs) have gained much importance. In WSNs, the routing of clusters has gained more interest. However, there is still a problem with the hotspot. One way to address this issue is uneven clustering. In these, nodes closer to the base station have the smallest cluster size. It decreases the relay pressure of the nodes which are close to the base station. In this paper, the unequal clustering routing based on fuzzy logic and bat algorithm is proposed, that is, FUCBR. Relative intra‐cluster costs and relative inter‐cluster costs are used in a very innovative manner. Fuzzy logic is used to create unequal clusters while the bat algorithm is used for multi‐hop routing. Unequal clustering minimizes the energy utilization for the member of the clusters. A novel probability technique is implemented in the cluster‐forming process to allow cluster members to determine which cluster they wish to join. The bat algorithm's objective function is carefully chosen to optimize the cluster heads' energy usage. After simulation, it was discovered that the proposed algorithm utilizes less energy and extends the network lifespan. The simulation results show that FUCBR's performance is 30% more improved than fuzzy‐based unequal clustering algorithm, genetic algorithm based unequal clustering and routing protocol, and grey wolf optimizer‐C algorithms. It is suitable for networks that require a long life.