Route discovery in cellular networks using soft computing techniques. (1st January 2013)

• Record Type: Journal Article
• Authors: Mala, C.; Gokul, A.; Babu, Anand; Kalyanasundaram, R.; Rajagopalan, Narendran
• Is Part Of: International journal of advanced intelligence paradigms. Volume 5:Number 1/2(2013)
• Page Start: 45
• Page End: 58
• Publication Date: 2013-01-01
• Subjects: cellular network -- ant colony optimisation -- ACO -- pheromone -- topology; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

A novel method for topology discovery of computer network using ant colony optimisation (ACO) is proposed. In this approach, the base station (BS) simulates the way ants forage for food to find out the routes to other BSs. The route discovered by each ant is associated with pheromone strength which in turn decides whether the route is the best or not. ACO applied to CN gives all the existing routes between the various BSs in a CN. Genetic algorithm (GA)-based optimisation is further applied to get the optimal path satisfying multiple constraints viz., number of hops, Poisson traffic distribution, buffer capacity, link delay, queuing delay, and residual bandwidth from the set of paths given by ACO. Our simulation results show that different network models viz., random model, unidirectional ring, bidirectional ring, star, and tree are explored faster using ACO and our scheme using ACO-GA outperforms the scheme without GA.