Design Of A Framework For Optimizing Bandwidth Allocation Of Video In Wireless Networks Using Hybrid Meta Heuristic Algorithm

Video transmission in wireless network poses several challenges such as latency, delayed throughput, slow convergence rate, high error rates, packet losses and many others which make it impossible for users to enjoy Quality of Service (QoS). Video in wireless network presents additional challenges due to unavailability of needed bandwidth. Bandwidth in any organization is a limited resource that is being competed for by the different users. Efficient and effective bandwidth allocation is a vital role in satisfying the QoS requirements for multimedia applications such as video streaming. This research work examined conventional and current techniques for bandwidth optimization. For better bandwidth use, conventional bandwidth allocation techniques are gradually being replaced with optimization algorithms using Genetic Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), Tabu Search (TS), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and so on. This work specifically addressed bandwidth challenges using hybrid algorithms of PSO+TS algorithms in optimizing the bandwidth allocation of Bells University of Technology, Ota, Ogun State, Nigeria. The PSO algorithm explores bandwidth by giving high priority to video traffic and low priority to other types of traffic (data traffic) while the TS algorithm exploits the bandwidth. The results were evaluated using CPU time and Worst Case Time Complexity of the algorithms. Results showed that with the proposed system, PSO+TS algorithm outperformed other individual algorithms of PSO and TS. Video traffics depending on resolution had higher priority levels and were assigned higher bandwidth while data traffic were assigned low bandwidth and as such video users will be able to stream conveniently with good QoS.