Admission Allotment Scheme Base Load Balancing Techniques for Clustering Routing in Wireless Sensor Network

Abstract

The Wireless Sensor Network, often known as WSN, has a wide range of applications spanning the commercial, indus-trial, and social spheres. WSN clustering is an efficient and low-cost way to extend the lifespan of a network while simultaneously improving its scalability, reliability and throughput. The performance of the WSN is hindered by lim-ited-power battery-driven sensor nodes and inaccurate cluster head (CH) location during the process of cluster crea-tion. This paper presents the Fuzzy C-mean algorithm (FCM) for clustering as well as the Artificial Bee Colony Algo-rithm (ABC) for CH selection and optimization. Both of these algorithms can be found here. A number of different clustering parameters are taken into consideration by the proposed ABC. These considerations include CH energy balancing, CH load balancing, the energy GINI coefficient, connectivity, as well as intra-cluster and inter-cluster distance. Afterward, an Ant Colony Optimization (ACO) that is more energy efficient is developed to transfer the data from CH to the base station (BS). Further, the novel Admission Allotment Scheme (AAS) it utilized for energy efficient intra-cluster communication to enhance the load balancing of the network. In relationship to the conventional state of the art, the newly suggested method delivers optimum cluster selection, which results in improved network lifespan, packet delivery ratio, and throughput.