Improving the Quality of Distributed Composite Service Applications

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



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Dionysios Efstathiou
Peter McBurney
Noël Plouzeau
Steffen Zschaler

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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)
https://doi.org/10.4230/OASIcs.ICCSW.2012.49

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.
Keywords
  • Service Composition
  • Optimisation
  • Dynamism
  • Evolution

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