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The authors 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. They propose a novel framework to characterize the video quality-based utility of the H.264 temporal and quality scalable video layers. Subsequently, they 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. They extend this framework to multiuser and multisubchannel scenario of 4G wireless networks. In this paper, they propose two novel schemes for long-term streaming video quality performance optimization based on maximum weight bipartite and greedy matching paradigms.
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