An Energy-Efficient Branch and Bound Optimization Algorithm for Large-Scale Software-Defined Networks

Software-defined network offers a programmable networking environment that redefines the management of conventional networking and can provide potential solutions for their well-known challenges. In SDN circumstances, energy becomes a major threatening factor that affects both the reliability of the network and the sustainability of its connections. Energy depletion in SDN is still a major concern considering the ever-changing network constraints and rapid growth in the number of networking devices. This research article introduces a novel energy-efficient branch-and-bound optimization (EE-BBO) algorithm, designed for large-scale software-defined networks to overcome the challenges faced by existing approaches. The objective of the EE-BBO algorithm is to minimize the energy consumption across the SDN networks and improve the network performance. The proposed algorithm computes the lower bounds for prioritizing nodes, classifies them based on their probable, and intelligently forwards packets to choose the most energy-efficient route. The algorithm is implemented on Mininet, using Floodlight as the SDN controller and OpenFlow as the communication protocol. The results of simulations showed that the proposed EE-BBO algorithm outperforms the current benchmarked methods in terms of energy consumption by 9-19%, packet loss by 15-28%, and enhancing network lifetime by 14-25%.