2 / 2022-08-31 12:22:53

A NOVEL CLUSTER HEAD SELECTION ALGORITHM BASED ON FUZZY CLUSTERING (FC) AND MODIFIED GREY WOLF OPTIMIZATION (MGWO)

Modified Grey Wolf Optimization (MGWO), Wireless Sensor Network (WSN), Particle Swarm Optimization (PSO), Fuzzy Clustering (FC), Low-Energy Adaptive Clustering Hierarchy (LEACH).

The goal of a Wireless Sensor Network (WSN) is to extend the network's life cycle, and topology control is critical to this goal. Particle Swarm Optimization is used to pick cluster heads based on Particle Swarm Optimization(PSO). In high-dimensional space, PSO is simple to slip into a local optimum, and the iterative process has a poor convergence rate. Propose a technique based on Fuzzy Clustering (FC) preprocessing and Modified Grey Wolf Optimization to address this problem (MGWO). First, the FC algorithm is used to create initial clustering for sensor nodes based on their geographical locations, where each sensor node belongs to a cluster with a given probability, and the number of first clusters is studied and discussed.In addition, the fitness function is created with WSN's energy consumption and distance aspects in mind. Finally, the MGWO is used to determine the CH nodes in hierarchical architecture. Experiments reveal that, when compared to standard methods, the proposed strategy was successful in lowering node mortality and prolonging the network life cycle.