Improved Coot Optimization Algorithm Based Energy Aware Multi-Hop Routing Protocol for Vehicular Adhoc Networks

Intelligent Transportation system becomes a hot research topic, afterwards Internet of Things (IoT)-based sensors have been efficiently integrated with vehicular Adhoc networks (VANET). Routing is a challenging issue in VANET to enable the effectual communication of data. Computational Intelligence (CI) is an emerging field that applies or develops a set of nature-inspired algorithms and methodologies to overcome challenging problems in real-time. The algorithms and methodologies are more commonly applied to manage complex engineering problems for which the traditional or mathematical modelling method is ineffective. Therefore, this study develops an Improved Coot Optimization Algorithm based Energy Aware Multi-Hop Routing Protocol (ICOA-EAMHRP) for VANET. The proposed ICOA-EAMHRP model is concentrated on the effectual detection of optimal routes in a short duration by the use of distinct VANET parameters. The proposed ICOA-EAMHRP model initially clusters the vehicles using a weighted-based clustering (WBC) scheme. For the route selection process, the ICOA-EAMHRP model follows the concept of two distinct modes of bird movement on the water surface such as regular and irregular. In addition, the ICOA-EAMHRP model derives a fitness function involving distinct input parameters such as Euclidean distance, mobility, bandwidth, and energy. To validate the improved performance of the ICOA-EAMHRP model, a detailed experimental analysis is carried out. The comparative study reported the enhanced performance of the ICOA-EAMHRP model over existing routing protocols.