QoS control strategies for high-quality video processing

C.C. Wüst, E.F.M. Steffens, W.F.J. Verhaegh, R.J. Bril, C. Hentschel

Research output: Contribution to journalArticleAcademicpeer-review

43 Citations (Scopus)


Video processing in software is often characterized by highly fluctuating, content-dependent processing times, and a limited tolerance for deadline misses. We present an approach that allows close-to-average-case resource allocation to a single video processing task, based on asynchronous, scalable processing, and QoS adaptation. The QoS adaptation balances different QoS parameters that can be tuned, based on user-perception experiments: picture quality, deadline misses, and quality changes. We model the balancing problem as a discrete stochastic decision problem, and propose two solution strategies, based on a Markov decision process and reinforcement learning, respectively. We enhance both strategies with a compensation for structural (non-stochastic) load fluctuations. Finally, we validate our approach by means of simulation experiments, and conclude that both enhanced strategies perform close to the theoretical optimum.
Original languageEnglish
Pages (from-to)7-29
JournalReal-Time Systems
Issue number1-2
Publication statusPublished - 2005


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