Pigeon Inspired Optimization Based Centroid Selection in TGVFCMS for Energy-Efficient Wireless Sensor Network

Abstract

Wireless Sensor Network (WSN) includes large quantities of sensing node used in various situations to collect data. WSN considers applications to collect data from remote locations, for example in environment surveillance, military, transport protection, etc. An energy efficient routing protocol is essential to handle the discharged electricity of the system and to minimize traffic and upstairs during data broadcast phases to fulfill the sensing, communication and processing tasks of the WSN. The biggest problem in the WSN is that energy resources are small. In this study, an energy-efficient routing protocol improves energy efficiency with the life span of sensor nodes by using optimization algorithm Pigeon Inspired Optimization (PIO). Clustering technique i.e. Total Generalized Variation Fuzzy c-means clustering (TGVFCMS) is used to select the Cluster Head (CH) and CH folds and bandage the information and direct it to the board node. By its fitness feature, PIO helps to initialize the centroid. After MATLAB simulation, the energy consumption rate was reduced to 25.03% while using PIO. Finally, comparisons are made between the work proposed and the existing current work to assess the effectiveness of the work proposed.