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

Journal article


Azevedo, Leonildo Jose de Melo de, Estrella, Julio C., Toledo, Claudia F. Motta and Reiff-Marganiec, Stephan 2020. A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3006171
AuthorsAzevedo, Leonildo Jose de Melo de, Estrella, Julio C., Toledo, Claudia F. Motta and Reiff-Marganiec, Stephan
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.

KeywordsCloud Computing Ecosystem; Metaheuristics; Multi-Objective Optimisation; SLA; QoS
Year2020
JournalIEEE Access
PublisherIEEE
ISSN2169-3536
Digital Object Identifier (DOI)https://doi.org/10.1109/ACCESS.2020.3006171
Web address (URL)http://hdl.handle.net/10545/624961
hdl:10545/624961
Publication dates30 Jun 2020
Publication process dates
Deposited09 Jul 2020, 08:08
Accepted24 Jun 2020
ContributorsUniversity of São Paulo (USP), São Carlos, SP, Brazil and University of Derby
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