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        <identifier>oai:drops-oai.dagstuhl.de:7140</identifier>
        <datestamp>2024-03-06T11:04:59Z</datestamp>
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          <dc:title>Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact)</dc:title>
          <dc:creator>Maggio, Martina</dc:creator>
          <dc:creator>Papadopoulos, Alessandro Vittorio</dc:creator>
          <dc:creator>Filieri, Antonio</dc:creator>
          <dc:creator>Hoffmann, Henry</dc:creator>
          <dc:subject>self-adaptive software</dc:subject>
          <dc:subject>video encoding</dc:subject>
          <dc:subject>comparison</dc:subject>
          <dc:subject>control theory</dc:subject>
          <dc:description>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.&#13;
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.&#13;
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.&#13;
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.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Martina Maggio and Alessandro Vittorio Papadopoulos and Antonio Filieri and Henry Hoffmann</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)</dc:relation>
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          <dc:identifier>doi:10.4230/DARTS.3.1.2</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-71408</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/DARTS.3.1.2</dc:identifier>
          <dc:language>eng</dc:language>
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