Software-Defined Networking’s Adaptive Load Optimisation Technique for Multimedia Applications with Multi-Controller Utilisation
Pardeep Singh Tiwana, Jaspreet Singh · 2023
Modern networking settings’ growing need for multimedia applications has sparked research into cutting-edge methods to improve network efficiency and resource utilization. A potential model that decouples the control and data planes to allow for centralized management and programmability has been developed called software-defined networking (SDN). The adaptive load optimization technique for multimedia applications with multi-controller utilization in SDN is presented in this research as being novel. The key to this method is its adaptive load optimization mechanism, which intelligently distributes network resources according to current traffic patterns and application needs. The method detects network congestion and proactively redistributes loads across network segments using machine learning and optimization techniques. For multimedia applications, this guarantees optimum resource utilization, reduces latency, and improves Quality of Service (QoS). The suggested approach shows its efficiency in improving the performance of multimedia applications through comprehensive simulations and testing in a variety of network conditions. Results show better throughput, decreased latency, and effective resource utilisation when compared to conventional static load balancing methods. Even in big and complicated network installations, the multi-controller architecture demonstrates its value by maintaining stability and responsiveness.