G-MOHRA: Green Multi-Objective Hybrid Routing Algorithm for Wireless Sensor Networks

Abstract

In Wireless Sensor Networks (WSNs), multi-objective optimization comprises more than one objective function to be improved simultaneously where there is a compromise between two or more contradictory objectives. The optimization method must be energy competent in terms of utilization and communication. This paper proposes a novel multi-objective optimization method known as Green (Energy Efficient)-Multi-Objective Hybrid Routing Algorithm (G-MOHRA) in WSNs. G-MOHRA uses hierarchical clustering. The information is dispatched using the finest path that uses a weighted average of various metrics in order to achieve energy efficiency and energy stability in the entire network. G-MOHRA uses various metrics such as Average Energy consumption (AEC), Control Overhead, Reaction Time, Link Quality Indicator (LQI), and HOP Count for identifying the best path from source to sink. In this paper, G-MOHRA uses objective functions that are said to be conflicting and provides Pareto optimal solutions. The performance of G-MOHRA is evaluated through intensive simulation and equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA). The metrics such as AEC, Residual Energy, Packet Delivery Ratio, Jitter, and Normalized Routing Load are used for comparison. Performance of G-MOHRA has been observed to outclass SHRP and DyMORA. It improves the Packet Delivery Ratio by 18.72% as compared to SHRP and 24.98 % as compared to DyMORA. G-MOHRA outperforms SHRP and DyMORA in terms of Average Energy Consumption by a factor of 19.79 % and 15.52 % as compared to SHRP and DyMORA respectively.