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DOI: 10.4230/OASIcs.ICCSW.2012.49

Improving the Quality of Distributed Composite Service Applications

Authors: Dionysios Efstathiou, Peter McBurney, Noël Plouzeau, and Steffen Zschaler

Published in: OASIcs, Volume 28, 2012 Imperial College Computing Student Workshop

Abstract

Dynamic service composition promotes the on-the-fly creation of value-added applications by combining services. Large scale, dynamic distributed applications, like those in the pervasive computing domain, pose many obstacles to service composition such as mobility, and resource availability. In such environments, a huge number of possible composition configurations may provide the same functionality, but only some of those may exhibit the desirable non-functional qualities (e.g. low battery consumption and response time) or satisfy users' preferences and constraints. The goal of a service composition optimiser is to scan the possible composition plans to detect these that are optimal in some sense (e.g. maximise availability or minimise data latency) with acceptable performance (e.g. relatively fast for the application domain). However, the majority of the proposed optimisation approaches for finding optimal composition plans, examine only the Quality of Service of each participated service in isolation without studying how the services are composed together within the composition. We argue that the consideration of multiple factors when searching for the optimal composition plans, such as which services are selected to participate in the composition, how these services are coordinated, communicate and interact within a composition, may improve the end-to-end quality of composite applications.

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Dionysios Efstathiou, Peter McBurney, Noël Plouzeau, and Steffen Zschaler. Improving the Quality of Distributed Composite Service Applications. In 2012 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 28, pp. 49-55, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{efstathiou_et_al:OASIcs.ICCSW.2012.49,
  author =	{Efstathiou, Dionysios and McBurney, Peter and Plouzeau, No\"{e}l and Zschaler, Steffen},
  title =	{{Improving the Quality of Distributed Composite Service Applications}},
  booktitle =	{2012 Imperial College Computing Student Workshop},
  pages =	{49--55},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-48-4},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{28},
  editor =	{Jones, Andrew V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2012.49},
  URN =		{urn:nbn:de:0030-drops-37649},
  doi =		{10.4230/OASIcs.ICCSW.2012.49},
  annote =	{Keywords: Service Composition, Optimisation, Dynamism, Evolution}
}

Document

DOI: 10.4230/OASIcs.ICCSW.2012.62

Mechanisms for Opponent Modelling

Authors: Christos Hadjinikolis, Sanjay Modgil, Elizabeth Black, and Peter McBurney

Published in: OASIcs, Volume 28, 2012 Imperial College Computing Student Workshop

Abstract

In various competitive game contexts, gathering information about one's opponent and relying on it for planning a strategy has been the dominant approach for numerous researchers who deal with what in game theoretic terms is known as the best response problem. This approach is known as opponent modelling. The general idea is given a model of one's adversary to rely on it for simulating the possible ways based on which a game may evolve, so as to then choose out of a number of response options the most suitable~in relation to one's goals. Similarly, many approaches concerned with strategising in the context of dialogue games rely on such models for implementing and employing strategies. In most cases though, the methodologies and the formal procedures based on which an opponent model may be built and updated receive little attention, as they are usually left implicit. In this paper we assume a general framework for argumentation-based persuasion dialogue, and we rely on a logical conception of arguments - based on the recent ASPIC^+ model for argumentation - to formally define a number of mechanisms based on which an opponent model may be built, updated, and augmented.

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Christos Hadjinikolis, Sanjay Modgil, Elizabeth Black, and Peter McBurney. Mechanisms for Opponent Modelling. In 2012 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 28, pp. 62-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{hadjinikolis_et_al:OASIcs.ICCSW.2012.62,
  author =	{Hadjinikolis, Christos and Modgil, Sanjay and Black, Elizabeth and McBurney, Peter},
  title =	{{Mechanisms for Opponent Modelling}},
  booktitle =	{2012 Imperial College Computing Student Workshop},
  pages =	{62--68},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-48-4},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{28},
  editor =	{Jones, Andrew V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2012.62},
  URN =		{urn:nbn:de:0030-drops-37663},
  doi =		{10.4230/OASIcs.ICCSW.2012.62},
  annote =	{Keywords: dialogue, strategies, argumentation, opponent model}
}

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Improving the Quality of Distributed Composite Service Applications

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Mechanisms for Opponent Modelling

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