QoS Guaranteed Intelligent Routing Using Hybrid PSO-GA in Wireless Mesh Networks

TL;DR

This paper introduces a hybrid PSO-GA algorithm to optimize QoS-aware routing in wireless mesh networks, effectively balancing convergence speed and solution quality amid dynamic network conditions.

Contribution

It proposes a novel hybrid PSO-GA approach that combines strengths of both algorithms to improve QoS-constrained routing in wireless mesh networks.

Findings

Hybrid PSO-GA outperforms individual PSO and GA in convergence speed.

The approach effectively satisfies QoS constraints like bandwidth and delay.

Simulation results demonstrate better reliability and reduced convergence time.

Abstract

In Multi-Channel Multi-Radio Wireless Mesh Networks (MCMR-WMN), finding the optimal routing by satisfying the Quality of Service (QoS) constraints is an ambitious task. Multiple paths are available from the source node to the gateway for reliability, and sometimes it is necessary to deal with failures of the link in WMN. A major challenge in a MCMR-WMN is finding the routing with QoS satisfied and an interference free path from the redundant paths, in order to transmit the packets through this path. The Particle Swarm Optimization (PSO) is an optimization technique to find the candidate solution in the search space optimally, and it applies artificial intelligence to solve the routing problem. On the other hand, the Genetic Algorithm (GA) is a population based meta-heuristic optimization algorithm inspired by the natural evolution, such as selection,mutation and crossover. PSO can easily fall into a local optimal solution, at the same time GA is not suitable for dynamic data due to the underlying dynamic network. In this paper we propose an optimal intelligent routing, using a Hybrid PSO-GA, which also meets the QoS constraints. Moreover, it integrates the strength of PSO and GA. The QoS constraints, such as bandwidth, delay, jitter and interference are transformed into penalty functions. The simulation results show that the hybrid approach outperforms PSO and GA individually, and it takes less convergence time comparatively, keeping away from converging prematurely. Keywords: Wireless mesh networks, Multi-radio, Multi-channel, Particle swarm optimization, Genetic algorithm, Quality of service.