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• W2789240493 abstract "Abstract Cloud computing has emerged as a new powerful service delivery model to cope with resource challenges and to offer various on‐demand services (eg, software, storage, network, etc.). Software as a Service (SaaS) is one of the most popular service models. To meet the increasing demands of users, SaaS can be offered in a composite form. Although this approach offers some advantages like flexibility and reusability, it raises a question about how to manage composite SaaS in the distributed and the highly dynamic cloud environment. In this paper, we address one of the major SaaS resource management issues referred to as SaaS placement problem. As existing efforts only focus on SaaS placement problem from the perspective of resources utilization to optimize SaaS performance and minimize resource usage, in this paper, we also incorporate security concerns in SaaS placement strategy. In fact, security risk is one of the major factors influencing the efficiency of the composite SaaS. We adopt a multi‐swarm variant of particle swarm optimization to propose a security‐aware SaaS placement method. Also, a cooperative learning strategy is hybridized to the placement algorithm, which makes information of best candidate servers be used more effectively to generate better placement plan. Experiments show that our solution outperforms existing SaaS placement approaches." @default.
• W2789240493 created "2018-03-29" @default.
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• W2789240493 date "2018-01-17" @default.
• W2789240493 modified "2023-10-09" @default.
• W2789240493 title "Security-aware SaaS placement using swarm intelligence" @default.
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• W2789240493 doi "https://doi.org/10.1002/smr.1932" @default.
• W2789240493 hasPublicationYear "2018" @default.
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