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Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact)

Authors: Martina Maggio, Alessandro Vittorio Papadopoulos, Antonio Filieri, and Henry Hoffmann

Published in: DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)

Abstract

This paper presents an adaptive video encoder that can be used to compare the behavior of different adaptation strategies using multiple actuators to steer the encoder towards a global goal, composed of multiple conflicting objectives. A video camera produces frames that the encoder manipulates with the objective of matching some space requirement to fit a given communication channel. A second objective is to maintain a given similarity index between the manipulated frames and the original ones. To achieve the goal, the software can change three parameters: the quality of the encoding, the noise reduction filter radius and the sharpening filter radius. In most cases the objectives - small encoded size and high quality - conflict, since a larger frame would have a higher similarity index to its original counterpart. This makes the problem difficult from the control perspective and makes the case study appealing to compare different adaptation strategies.

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Martina Maggio, Alessandro Vittorio Papadopoulos, Antonio Filieri, and Henry Hoffmann. Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact). In Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017). Dagstuhl Artifacts Series (DARTS), Volume 3, Issue 1, pp. 2:1-2:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{maggio_et_al:DARTS.3.1.2,
  author =	{Maggio, Martina and Papadopoulos, Alessandro Vittorio and Filieri, Antonio and Hoffmann, Henry},
  title =	{{Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact)}},
  pages =	{2:1--2:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  editor =	{Maggio, Martina and Papadopoulos, Alessandro Vittorio and Filieri, Antonio and Hoffmann, Henry},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.3.1.2},
  URN =		{urn:nbn:de:0030-drops-71408},
  doi =		{10.4230/DARTS.3.1.2},
  annote =	{Keywords: self-adaptive software, video encoding, comparison, control theory}
}

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DOI: 10.4230/DagRep.5.11.151

Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491)

Authors: Antonio Filieri, Marta Kwiatkowska, Sasa Misailovic, and Todd Mytkowicz

Published in: Dagstuhl Reports, Volume 5, Issue 11 (2016)

Abstract

Computing has entered the era of approximation, in which hardware and software generate and reason about estimates. Navigation applications turn maps and location estimates from hardware GPS sensors into driving directions; speech recognition turns an analog signal into a likely sentence; search turns queries into information; network protocols deliver unreliable messages; and recent advances promise that approximate hardware and software will trade result quality for energy efficiency. Millions of people already use software which computes with and reasons about approximate/probabilistic data daily. These complex systems require sophisticated algorithms to deliver accurate answers quickly, at scale, and with energy efficiency, and approximation is often the only way to meet these competing goals. Despite their ubiquity, economic significance, and societal impact, building such applications is difficult and requires expertise across the system stack, in addition to statistics and application-specific domain knowledge. Non-expert developers need tools and expertise to help them design, code, and verify these complex systems. The aim of this seminar was to bring together academic and industrial researchers from the areas of probabilistic model checking, quantitative software analysis, probabilistic programming, and approximate computing to share their recent progress, identify challenges in computing with estimates, and foster collaboration with the goal of helping non-expert developers design, code, and verify modern approximate and probabilistic systems.

Cite as

Antonio Filieri, Marta Kwiatkowska, Sasa Misailovic, and Todd Mytkowicz. Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491). In Dagstuhl Reports, Volume 5, Issue 11, pp. 151-179, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{filieri_et_al:DagRep.5.11.151,
  author =	{Filieri, Antonio and Kwiatkowska, Marta and Misailovic, Sasa and Mytkowicz, Todd},
  title =	{{Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491)}},
  pages =	{151--179},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{5},
  number =	{11},
  editor =	{Filieri, Antonio and Kwiatkowska, Marta and Misailovic, Sasa and Mytkowicz, Todd},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.11.151},
  URN =		{urn:nbn:de:0030-drops-58008},
  doi =		{10.4230/DagRep.5.11.151},
  annote =	{Keywords: approximation, model checking, performance, probability, program analysis, systems, verification}
}

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Documents authored by Filieri, Antonio

Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact)

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Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491)

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