A Comprehensive Analysis on Load Balancing of Software Defined Networking using Resource Optimization on AI-Based Applications

The article study applications of Artificial Intelligence (AI) within Software Defined Networks (SDN), aiming to optimize network functionality and resource utilization. Employing AI techniques can effectively manage network traffic distribution across diverse resources, enhancing operational efficiency and resource effectiveness. This paper conducts a comprehensive analysis of current practices, equitable workload distribution methods, and efficient resource utilization strategies within SDN environments. Utilizing clear plans, adaptable procedures, and sophisticated problem-solving mechanisms, the AI-driven system can efficiently address task distribution among network components, significantly enhancing performance compared to conventional methods. This study proposed an AI framework that can efficiently manage load balancing, ensuring system scalability, adaptability, and responsive growth. The proposed approach stands as an ideal solution for network administrators seeking automated, high-quality strategies to optimize resources in SDN setups that set our future directions to demonstrate.