Optimal H.264 Scalable Video Scheduling Policies for 3G/4G Wireless Cellular and Video Sensor Networks

We consider the problem of optimal H.264 scalable video scheduling, with an objective of maximizing the end-user video quality while ensuring fairness in 3G/4G broadband wireless networks and video sensor networks. We propose a novel framework to characterize the video quality-based utility of the H.264 temporal and quality scalable video layers. Subsequently, we formulate the scalable video scheduling framework as a Markov decision process (MDP) for long-term average video utility maximization and derive the optimal index based-scalable video scheduling policies ISVP and ISVPF towards video quality maximization. Further, we extend this framework to multiuser and multisubchannel scenario of 4G wireless networks. In this context, we propose two novel schemes for long-term streaming video quality performance optimization based on maximum weight bipartite and greedy matching paradigms. Simulation results demonstrate that the proposed algorithms achieve superior end-user video experience compared to competing scheduling policies such as Proportional Fairness (PF), Linear Index Policy (LIP), Rate Starvation Age policy (RSA), and Quality Proportional Fair Policy (QPF)