This analysis demonstrates improvements in network performance via software-defined networking, suggesting enhanced traffic engineering and load balancing strategies.
Software-Defined Networking (SDN) is revolutionizing network architecture by decoupling the control and data planes, enabling centralized control, programmability, and automation. This paper explores methods to optimize network performance through SDN, focusing on traffic engineering, load balancing, and dynamic routing. We present a comprehensive overview of existing techniques and propose an optimization framework that leverages real-time data analytics and machine learning to enhance throughput, reduce latency, and improve resource utilization. Experimental results from simulation environments demonstrate significant performance improvements when applying the proposed methods. This paper explores the role of SDN in optimizing network performance. It highlights key architectural components, examines practical implementation strategies, and evaluates performance metrics and case studies that demonstrate the effectiveness of SDN in real-world scenarios. Ultimately, the goal is to provide a comprehensive understanding of how SDN can be used to create smarter, more responsive, and efficient networks
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AliAbuhamra et al. (2025) studied this question.
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