A QoS based Routing Approach using Genetic Algorithms for Bandwidth Maximization in Network

TL;DR

This paper presents a genetic algorithm-based routing method that optimizes bandwidth and minimizes route length in dense networks by considering QoS parameters like delay, jitter, and loss.

Contribution

It introduces a novel QoS-aware routing approach using genetic algorithms with multi-point crossover and mutation for bandwidth maximization.

Findings

Higher probability of convergence to shortest path using GA

Effective bandwidth maximization along routes

Improved route selection based on QoS parameters

Abstract

This paper addresses the path selection problem from a known source to the destination in dense networks. The proposed solution for route discovery uses the genetic algorithm approach for a QoS based network. The multi point crossover and mutation helps in determining the optimal path and alternate path when required. The input to the genetic algorithm is a learnt module which is a part of the cognitive router that takes care of four QoS parameters. Here the set of nodes selected for routing is determined by delay, jitter and loss. On this graded surface of nodes selected, the bandwidth parameter is considered for path selection. The aim of the approach is to occupy the maximized bandwidth along the forward channels and minimize the route length. The population size is considered as fixed nodes participating in the network scenario, which will be limited to a known size of topology. The simulated results show that by using genetic algorithm (GA) approach the probability of convergence to shortest path is higher.