Video quality-of-service for consumer terminals - a novel system for programmable components

Hentschel, Christian; Bril, Reinder J.; Chen, Yingwei; Braspenning, Ralph; Lan, Tse-Hua

doi:10.1109/tce.2003.1261242

Cited by 16 publications

(3 citation statements)

References 14 publications

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“…Similarly, dynamic resource allocation also differs from resource management techniques, such as reservation-based resource management, that have been applied in the context of more traditional approaches to SVAs. Whereas our dynamic resource allocation mechanisms are unique, the architectural approach taken for SVAs on programmable platform is similar to, for example, Hentschel et al [2]. In particular, we also make a clear distinction between system and application responsibilities and address these responsibilities in dedicated components in the architecture of our system.…”

Section: Related Workmentioning

confidence: 99%

“…To enable costeffective media processing in software, scalable video algorithms (SVAs) have been conceived which allow trading resource usage against output quality at the level of individual frames, and complemented with dynamic resource management techniques [1]. The additional advantage of the latter approach is the ability to add functionality on already fully loaded platforms, albeit at lower quality of some functionalities, and to reuse hardware and software modules to support product families [2].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic resource allocation for real-time priority processing applications

Heuvel

Bril

Schiemenz

et al. 2010

IEEE Trans. Consumer Electron.

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Citation for published version (APA):Heuvel, van den, M. M. H. P., Bril, R. J., Schiemenz, S., & Hentschel, C. (2010). Dynamic resource allocation for real-time priority processing applications. IEEE Transactions on Consumer Electronics, 56 (2) Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement: www.tue.nl/taverne Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nl providing details and we will investigate your claim.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic resource allocation for real-time priority processing applications

Heuvel

Bril

Schiemenz

et al. 2010

IEEE Trans. Consumer Electron.

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“…, q 3 , in order of increasing quality, running on a TriMedia 1300 (180 MHz) processor (Slavenburg et al, 1996). This decoder, which is based on IDCT pruning, was made (Peng, 2001;Zhong et al, 2002), and was integrated in a demonstrator annex research platform (Hentschel et al, 2003;Otero Pérez and Nitescu, 2002). For each sequence we produced four processing-time traces, one for each quality level.…”

Section: Experimental Set-upmentioning

confidence: 99%

QoS Control Strategies for High-Quality Video Processing

et al. 2005

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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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