Optimized Resource Sharing for Federated Cloud Services with Desired Performance and Limited OpEx

Abozariba, Raouf and Amjad, Anas and Patwary, Mohammad (2017) Optimized Resource Sharing for Federated Cloud Services with Desired Performance and Limited OpEx. In: IEEE Global Communications Conference (GLOBECOM),, 4-8 December, Singapore. (In Press)

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Abstract

The provision of cloud resources to meet user demands in 5G wireless networks is a challenging task due to the high workload predicted to be experienced by cloud service providers (CSPs). Cloud federation has emerged as a paradigm to support CSPs with resource limitations by borrowing surplus resources of other CSPs in periods of high demands. The major concern of each CSP with resource limitations is to borrow resources from other federation participants in such a way that cloud services are provided to the end-users with a desired grade of service (GoS) as well as the overall profit is maximized. This paper proposes an efficient mechanism based on the merchant mode to dynamically facilitate optimal allocation of cloud resources, maximizing the profit of CSPs as well as improving the
GoS. The robustness of the proposed optimal scheme is evaluated by comparing it with the heuristic algorithm. The simulation results demonstrate that at each trading window, the proposed optimal scheme outperforms its heuristic counterpart. Moreover, after 50 trading windows, the proposed approach results in 43.5% gain in net profit to CSPs as well as facilitating 3.35% of additional resource.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cloud computing, cloud federation, internet of things, resource sharing, profit maximization.
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cloud Computing
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 01 Sep 2017 10:11
Last Modified: 01 Sep 2017 10:11
URI: http://www.open-access.bcu.ac.uk/id/eprint/5109

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