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QoS Control Strategies for High-Quality Video Processing

Published: 01 May 2005 Publication History

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.

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Published In

cover image Real-Time Systems
Real-Time Systems  Volume 30, Issue 1-2
May 2005
145 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 May 2005

Author Tags

  1. Markov decision process
  2. Quality of Service (QoS)
  3. multimedia
  4. overload
  5. reinforcement learning
  6. soft real time

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  • (2013)Adaptive real-time scheduling for legacy multimedia applicationsACM Transactions on Embedded Computing Systems10.1145/2362336.236235311:4(1-23)Online publication date: 1-Jan-2013
  • (2011)A Robust Mechanism for Adaptive Scheduling of Multimedia ApplicationsACM Transactions on Embedded Computing Systems10.1145/2043662.204367010:4(1-24)Online publication date: 1-Nov-2011
  • (2010)Control strategies for H.264 video decoding under resources constraintsACM SIGOPS Operating Systems Review10.1145/1842733.184274344:3(53-58)Online publication date: 17-Aug-2010
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