Modified smell detection algorithm for optimal paths engineering in hybrid SDN

Abstract

Optimal path engineering in hybrid software defined networking environments involves leveraging traditional networking and software defined capabilities to determine the most efficient paths for network traffic. In hybrid software defined networks, some parts of the network may be controlled by controllers, while others rely on traditional routing protocols. Leveraging the OpenFlow protocol, widely used in such deployments, to program flow entries in software defined switches is one approach to achieving optimal path engineering in hybrid software defined networks. By specifying specific rules and policies in the switches, we can control traffic forwarding behaviour and steer traffic along desired paths based on application requirements. In this work, the smell detection algorithm, a new variant of bio-inspired method, is adopted to explore its capability in routing. The new paradigm of smell detection agent, its architecture, protocols used, and the concept of hybrid defined network is also explained. A comprehensive experimental examination of within the controller, an algorithm based on smell detecting agents computes the most efficient route from where it began to the intended destination. Simulation results readily demonstrate the smell detection agent based technique's effective functioning in getting the optimum direction. In this work, bio-inspired algorithms outperformed conventional algorithms in terms of performance.