Optimization Based Multi-Objective Weighted Clustering For Remote Monitoring System in WSN

Wireless Sensor Network (WSN) is generally considered as a standout amongst the most critical advancements for the twenty-first century, it normally comprises multifunctional wireless sensor nodes, with detecting, communications, and calculation capacities. Clustering the random nodes in WSN is a challenging task with high performance. This paper presents the new clustering model to monitor the eco-friendly mobile network by clustering the sensor nodes and to enhance the Quality of Service of that optimal network in WSN. The proposed Multi-Objective Weighted Clustering model groups the arbitrary nodes and afterward the optimal network is achieved by the optimization of network parameters. For optimizing the network parameters, a metaheuristic algorithm i.e. Improved Fruit Fly Optimization is introduced. With the goal of assessing the Coverage Efficiency (CE) and network user satisfaction of the accomplished optimal mobile network in WSN, the remote sensor monitoring process is applied. Sensor monitoring helps to know the network users and furthermore to improve the CE of WSN, contrasted with existing work.