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 by user-perception experiments: picture quality, deadline misses, and quality changes. We model the balancing problem as a discrete stochastic decision problem, and propose two closely related solution strategies, for which the processing-time statistics are determined offline and at run time, 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 language | English |
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| Title of host publication | 16th Euromicro Conference on Real-Time Systems (ECRTS'04, Catania, Italy, June 30-July 2, 2004) |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 3-12 |
| ISBN (Print) | 0-7695-2176-2 |
| DOIs | |
| Publication status | Published - 2004 |