A survey paper on Ant Colony Optimization Routing algorithm for selecting Multiple Feasible Paths for Packet Switched Networks

• Published in: International journal of computer science issues Vol. 9; no. 2; p. 271
• Main Authors: Patel, Meenakshi R, Kubde, Babita
• Format: Journal Article
• Language: English
• Published: Mahebourg International Journal of Computer Science Issues (IJCSI) 01.03.2012
• Subjects: Algorithms; Ant colony optimization; Computer networks; Computer science; Mathematical analysis; Mathematical models; Networks; Routing (telecommunications); Switching theory
• ISSN: 1694-0814; 1694-0784

ACO algorithms for datagram networks was given by Di Caro & Dorigo, in year 1996. Basic mechanisms in typical ACO routing algorithms is Ant-like agents are proactively generated at the nodes to find/check paths toward assigned destinations Ants move hop-by-hop according to a exploratory routing policy based on the local routing .After reaching their destination, ants retrace their path and update nodes routing information according to the quality of the path. Routing information is statistical estimates of the time-to-go to the destination maintained in pheromone arrays. Data are probabilistically spread over the paths according to their estimated quality as stored in the pheromone variables. AntNet algorithms may cause the network congestion and stagnation as the routing table converges. In this paper we perform a survey on modified AntNet routing algorithm using Multiple Ant-Colony Optimization. Multiple ant colonies with different pheromone updating mechanism have different searching traits. By leveraging this feature, much of work is done by designing a set of adaptive rules to facilitate the collaboration between these colonies. This approach can balance the diversity and convergence of solutions generated by different ant colonies and also overcome the problem of Stagnation.