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    Semantic Similarity Model for Risk Assessment in Forming Cloud Computing SLAs

    Access Status
    Fulltext not available
    Authors
    Hussain, Omar
    Dong, Hai
    Singh, Jaipal
    Date
    2010
    Type
    Book Chapter
    
    Metadata
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    Citation
    Hussain, Omar and Dong, Hai and Singh, Jaipal. 2010. Semantic Similarity Model for Risk Assessment in Forming Cloud Computing SLAs, in Meersman, R. and Dillon, T.S. and Herrero, P. (ed), Lecture Notes in Computer Science, Volume 6427: On the Move to Meaningful Internet Systems (OTM 2010). pp. 843-860. Germany: Springer.
    Source Title
    Lecture notes in computer science, volume 6427: on the move to meaningful internet systems (OTM 2010)
    ISBN
    9783642169489
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/28292
    Collection
    • Curtin Research Publications
    Abstract

    Cloud computing has enabled users to access various resources and applications as a service and in return pay the provider only for the time for which they are used. Service Level Agreements (SLA) are formed between the user and provider to ensure that the required services and applications are delivered as expected. With the increase of public cloud providers, challenges such as availability, reliability, security, privacy and transactional risk demand detail assessment while forming SLAs. This paper focuses on one sub-category of transactional risk while forming SLAs; namely performance risk. We argue that performance risk assessment should be done by the user before entering into a SLA with a service provider. We propose to measure performance risk according to the specific context and assessment criteria with the aid of a semantic similarity model for the SLA requirement being negotiated in a cloud computing environment. We show through simulations that the performance risk analysis is more accurate using semantic similarity matching compared with risk analysis without semantic similarity matching.

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