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Performance Enhancement of OMP Algorithm for Compressed Sensing Based Sparse Channel Estimation in OFDM Systems Read chapter Read first chapter

2018 | OriginalPaper | Chapter

24. SCORS: Smart Cloud Optimal Resource Selection

Authors : Fahad Alsolami, Yaqoob Sayid, Nawal Zaied, Isaac Sayid, Iman Ismail

Published in: Information Technology - New Generations

Publisher: Springer International Publishing

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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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Metadata
Title
SCORS: Smart Cloud Optimal Resource Selection
Authors
Fahad Alsolami
Yaqoob Sayid
Nawal Zaied
Isaac Sayid
Iman Ismail
Copyright Year
2018
Book
Information Technology - New Generations

Print ISBN: 978-3-319-54977-4

Electronic ISBN: 978-3-319-54978-1

Copyright Year: 2018

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

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