ACOSDN-Ant Colony Optimization Algorithm for Dynamic Routing In Software Defined Networking

摘要

Recently, Software Defined Networking (SDN) is emerging to replace traditional network architecture management at a reduced cost. SDN aims to introduce a centralized intelligent network in a core controller. OpenFlow (OF) is considered the most commonly used southbound API in SDN. Existing routing optimization algorithms are effective but at high order of time and space complexity. This complexity opens the door for the researchers to use the heuristic techniques to optimize the dynamic routing in OF-based SDNs. There are few attempts to introduce intelligent optimization routing technique at SDN controller layer (SDN brain). This paper suggests a modified Ant Colony Optimization (ACO) algorithm called “ACOSDN” to optimize the dynamic routing in SDNs. The suggested algorithm is compared to other related work and other routing techniques in SDN, the effectiveness is measured and the results show that the algorithm is able to handle dynamic network changes, reduce the network congestion and achieve higher throughput associated with a lower delay and packet loss rates.