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    A QOS-based service retrieval methodology for the digital ecosystems

    134803_18078_PUB-CBS-EEB-MC-50090.pdf (1.119Mb)
    Access Status
    Open access
    Authors
    Dong, Hai
    Hussain, Farookh Khadeer
    Chang, Elizabeth
    Date
    2009
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Dong, Hai and Hussain, Farookh Khadeer and Chang, Elizabeth. 2009. A QoS-based service retrieval methodology for the digital ecosystems. International Journal of Web and Grid Services. 5 (3): pp. 261-283.
    Source Title
    International Journal of Web and Grid Services
    DOI
    10.1504/IJWGS.2009.028345
    Additional URLs
    http://www.inderscience.com/search/index.php?action=record&rec_id=28345
    ISSN
    17411106
    Faculty
    Curtin Business School
    The Digital Ecosystems and Business Intelligence Institute (DEBII)
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/21461
    Collection
    • Curtin Research Publications
    Abstract

    The emergence of the World Wide Web and its influence on the field of industry, commerce, healthcare etc. has led to an innovative, dynamic, open, collaborative and interactive environment - Digital Ecosystems. Whereas service plays an important role in the Digital Ecosystems, there is no technology available to retrieve the heterogeneous and geographically dispersed services. Additionally, no methodology has been proposed in the literature that can distinguish or rank the services based on the Quality of Services(QoS). In order to address these issues, we propose a semantic service retrieval engine which incorporates a novel semantic QoS evaluation methodology. The salient feature of this methodology, that sets it apart from any other QoS evaluation methodologies, is that the evaluation of the service and the subsequent quantification of QoS is a combination of subjective QoS measures and objective QoS measures. Another salient feature of our proposed methodology is that it enables the domain-specific ranking of services. Finally, an online prototype is implemented to evaluate our methodology, the results of which are discussed in this paper.

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