Title: A QoS-based routing approach using genetic algorithms for bandwidth maximisation in networks

Authors: T.R. Gopalakrishnan Nair; Kavitha Sooda; R. Selvarani

Addresses: Technology and Information Management, PMU, KSA, DSI, Bangalore-78, (Sabbatical), India ' Nitte Meenakshi Institute of Technology, P.B. No. 6429, Gollahalli, Govindapura, Yelahanka, Banglore-64, India ' King Abdul Aziz University Saudi Arabia, M.S. Ramaiah Institute of Technology, Bangalore – 560054 (Sabbatical), India

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 maximised bandwidth along the forward channels and minimise 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.

Keywords: routing; cognition; genetic algorithms; multipoint crossover; bandwidth maximisation; QoS; quality of service; mutation; optimal path; intelligent systems; elitism; path selection; dense networks; delay; jitter; loss; simulation; cognitive router.

DOI: 10.1504/IJAISC.2014.059289

International Journal of Artificial Intelligence and Soft Computing, 2014 Vol.4 No.1, pp.80 - 94

Accepted: 25 May 2013
Published online: 28 Jun 2014 *

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