Convergence Factor and Position Updating Improved Grey Wolf Optimization for Multi-constraint and Multipath QoS Aware Routing in Mobile Adhoc Networks
Sulaiman Ghaleb, Vasanthi Varadharajan · International journal of intelligent engineering and systems · 2020
Optimal shortest path routing is one of the most common problems in Mobile adhoc networks (MANETs).Energy and delay are the two vital factors that determine the optimal shortest paths for multipath communication.Although many algorithms have tried to solve this shortest path problems, the cost and link disconnection are mostly neglected in real-time applications.This paper provokes the thought of including the multiple Quality-of-Service (QoS) parameters such as energy, delay, link quality and network lifetime as the objective parameters in selecting the optimal shortest paths.Modelling the objective cost function as an optimization problem based on these parameters, the Multi-objective Improved Grey Wolf Optimization (IGWO) algorithm based Dynamic Source Routing (DSR) protocol is developed to resolve it.IGWO is designed by modifying the location updating equations and the convergence factor to resolve the GWO local optimum problem and improve its convergence speed.First, the possible paths in the network are discovered and the fitness is evaluated for each routing path.Then the paths are sorted using the IGWO algorithm and then the optimal paths are determined with increased energy efficiency and reduced delay.Experimental results indicate the efficiency of the proposed IGWO-DSR protocol through 8.4% less delay, 3% high throughput, 11% less energy consumption, 14% increased lifetime, and reduced hop count by 1 and 15dB increased PSNR than the original GWO algorithm.The proposed IGWO-DSR also outperforms the other existing routing algorithms.