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    Probabilistic analysis of QoS-aware service composition with Explicit Environment Models

    Zhou, Y. and Han, Tingting and Chen, Taolue and Zhou, S. (2020) Probabilistic analysis of QoS-aware service composition with Explicit Environment Models. IET Software 14 (1), pp. 59-71. ISSN 1751-8806.

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    Abstract

    Service composition is one of the primary ways to provide value-added services on the Internet. Quality-of-Service (QoS) represents a crucial indicator for the underlying composition policy adoption, but it is highly influenced by various environmental factors. Existing composition strategies rarely take the influence of environment into consideration explicitly, which may lead to sub-optimal composition policies in a dynamic environment. In this paper, a model-based service composition approach is proposed. Given the user request, it is possible to first find a set of matching abstract web services (AWSs), and then pull relevant concrete web services (CWSs) based on the AWSs. The set of CWSs can be modelled as a Markov decision process (MDP). In addition, we model the environment as a fully probabilistic system, capturing changes of environment probabilistically. The environment model can be further composed with the MDP from the service models, obtaining a monolithic MDP. The policy of which corresponds the selection of concrete services. We demonstrate how probabilistic verification techniques can be used to find the optimal service selection strategy against their QoS and the environment change. A distinguished feature of our approach is that the QoS of services, as well as the dynamic of environment change, are made parametric, so that the formal analysis is adaptive to the environment which is of paramount importance for autonomous and self-adaptive systems. Examples and experiments confirm the feasibility of our approach.

    Metadata

    Item Type: Article
    Additional Information: "This paper is a postprint of a paper submitted to and accepted for publication in an IET journal and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library".
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Data Analytics, Birkbeck Institute for
    Depositing User: Tingting Han
    Date Deposited: 08 Nov 2019 14:46
    Last Modified: 09 Aug 2023 12:47
    URI: https://eprints.bbk.ac.uk/id/eprint/29829

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