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Abstract

The Software-Defined Networking (SDN) paradigm decouples the control and the data plane. One of the most significant challenges in this paradigm is SDN controller placement optimization, since improper placement may dramatically influence latency, load balancing, and network resilience. The paper proposes the Improved Harmony Search Algorithm (IHSA) as a new approach for the placement of SDN controllers. To overcome the disadvantages of conventional optimization methods like HSA, GA, and PSO, adaptive parameter tuning, dynamic harmony memory management, and updating rules for enhanced memory are incorporated into the IHSA. The complete simulations of IHSA over small, medium, and large-scale SDN topologies have shown its robust supremacy in performance compared to the benchmark algorithms, which provide up to 23.5% less latency along with significant improvements in load-balancing and convergence-time. The optimization results of IHSA are well supported by the statistical validity based on the p-values and confidence intervals. The algorithm is scalable, adaptive, and very efficient. Hence, it makes a more realistic solution for real-time and dynamic SDN environments. The results show that IHSA has the potential to improve network performance in latency-sensitive applications such as IoT, cloud computing, and telecommunications, thus opening up resilient and high-performance network infrastructures. This is a practical application of IHSA, and subsequently, the recommendation given through this study is for its integration with datasets and machine learning techniques from real world to further improve optimization.

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