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    A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem

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    IEEE_ACCESS_Leonildo_NSGA-4.pdf
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    Authors
    Azevedo, Leonildo Jose de Melo de
    Estrella, Julio C.
    Toledo, Claudia F. Motta
    Reiff-Marganiec, Stephan
    Affiliation
    University of São Paulo (USP), São Carlos, SP, Brazil
    University of Derby
    Issue Date
    2020-06-30
    
    Metadata
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    Abstract
    The cloud ecosystem provides transformative advantages that allow elastically offering ondemand services. However, it is not always possible to provide adequate services to all customers and thus to fulfill service level agreements (SLA). To enable compliance with these agreements, service providers leave the customer responsible for determining the service settings and expect that the client knows what to do. Some studies address SLA compliance, but the existing works do not adequately address the problem of resource allocation according to clients’ needs since they consider a limited set of objectives to be analyzed and fulfilled. In previous work, we have already addressed the problem considering a single-objective approach. In that work, we identified that the problem has a multi-objective characteristic since several attributes simultaneously influence the SLA agreement, which can lead to conflicts. This paper proposes a multi-objective combinatorial optimization approach for computational resources provisioning, seeking to optimize the efficient use of the infrastructure and provide the client with greater flexibility in contract closure.
    Citation
    De Azevedo, L.J.D.M., Estrella, J.C., Toledo, C.F.M. and Reiff-Marganiec, S., (2020). 'A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem.' IEEE Access, pp. 1-11.
    Publisher
    IEEE
    Journal
    IEEE Access
    URI
    http://hdl.handle.net/10545/624961
    DOI
    10.1109/ACCESS.2020.3006171
    Additional Links
    https://ieeexplore.ieee.org/abstract/document/9129701
    Type
    Article
    Language
    en
    EISSN
    2169-3536
    ae974a485f413a2113503eed53cd6c53
    10.1109/ACCESS.2020.3006171
    Scopus Count
    Collections
    Department of Electronics, Computing & Maths

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