Improved Routing with Optimized Group Head Selection using Genetic Algorithm for Heterogeneous Distributed Network

Abstract

 Devices in Internet of Things (IoT) operates by battery source and prone to energy drain as they started to communicate. Battery power usually affects the lifetime of these IoT devices. Hence routing with minimum energy is a major constrain of these IoT environment. The work is concerned with improved Group Head (GH) selection over Distributed Energy- Efficient protocol with Genetic Algorithm (DEEC-GA) to decrease nodal energy demand and increase its network lifetime. The proposed method is compared with existing Distributed Energy Efficient Clustering (DEEC) and Enhanced DEEC (EDEEC) and performance metrics such as Network Lifetime, number of lively nodes and data transmission sent to Base Station (BS) and Group Head for different probability is analyzed and found DEEC-GA outperforms both DEEC and EDEEC.