Abstract
Software-Defined Networks (SDN) represent an efficient approach for managing large-scale networks, aiming to enhance resource use, performance, cost efficiency, and quality of service for dynamic services. By segregating the control plane and utilizing a centralized software controller, SDN offers notable capabilities in software development, programmability, and flexibility. Nevertheless, balancing energy efficiency and processing power remains a key challenge. This paper introduces an interactive scheme within the SDN controller, employing the krill herd meta-heuristic algorithm for optimization-based programming. The proposed method emphasizes the interaction between load balancing (LB) and energy efficiency, leveraging control plane data and virtual machine (VM) updates to derive optimal solutions. Simulation results illustrate an average 13.5 % enhancement in SDN load balancing, a 25.9 % improvement in energy efficiency, and an approximate 20 % performance boost, showcasing the effectiveness of the proposed approach.
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