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SCORS: Smart Cloud Optimal Resource Selection

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 558))

Abstract

Cloud storages have recently increased rapidly in many organizations as they provide many benefits and advantages for the users. These advantages include easiness in use, unlimited capacity in storage, scalability and cost effectiveness. This has motivated the concerns regarding the cloud issues including cost, performance and security. Many different schemes have been proposed to address the issues of cloud storage. Each scheme considers these issues from different perspectives without employing an optimal solution that fully satisfies the user requirements. In real world applications, the client's objectives to move to cloud storage vary from single objective to several conflicting objectives. As a result, there is a need to find a tradeoff setup for a multiple cloud storage scheme. This paper proposed Smart Cloud Optimal Resource Selection (SCORS) scheme by applying non-dominated sorting genetic algorithm (NSGA-2) to resolve the user's conflicting requirements. Our optimal solution facilitates setting up multiple cloud storages in an optimized way based on the objectives specified. Since each user has different objectives, all combinations of cloud storage client needs are collected and transformed into different multi-objective optimization problems with constraints and bounds. Experiment results show that SCORS scheme determine the optimal solution from the set of feasible solutions in an efficient way.

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Correspondence to Fahad Alsolami .

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Alsolami, F., Sayid, Y., Zaied, N., Sayid, I., Ismail, I. (2018). SCORS: Smart Cloud Optimal Resource Selection. In: Latifi, S. (eds) Information Technology - New Generations. Advances in Intelligent Systems and Computing, vol 558. Springer, Cham. https://doi.org/10.1007/978-3-319-54978-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-54978-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54977-4

  • Online ISBN: 978-3-319-54978-1

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