QoS control strategies for high-quality video processing

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

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43 Citations (Scopus)

Abstract

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
Volume30
Issue number1-2
DOIs
Publication statusPublished - 2005

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    Wüst, C. C., Steffens, E. F. M., Verhaegh, W. F. J., Bril, R. J., & Hentschel, C. (2005). QoS control strategies for high-quality video processing. Real-Time Systems, 30(1-2), 7-29. https://doi.org/10.1007/s11241-005-0502-1