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BWSLICER: A bandwidth slicing framework for cloud data centers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-3548-2973
University of Houston Victoria, USA..
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9194-010X
Beirut Arab University, LBN..
2020 (English)In: Future Generation Computer Systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 112, p. 767-784Article in journal (Refereed) Published
Abstract [en]

Bandwidth allocation is an important and influential factor in enhancing the performance of the data centers' nodes. In this paper we propose bwSlicer, a framework for bandwidth slicing in cloud data centers, that sheds light on the virtues of effective dynamic bandwidth allocation on improving the system performance and energy efficiency. Three algorithms are investigated to deal with this issue. In the first algorithm, called Fair Bandwidth Reallocation (FBR), two virtual machines co-hosted on the same node conditionally exchange bandwidth slices based on their requirements. The second algorithm, called Required Bandwidth Allocation (RBA), periodically monitors the co-hosted virtual machines and adds/removes bandwidth slices for each of them based on their bandwidth utilization. The third algorithm, called Divide Bandwidth Reallocation (DBR), divides the bandwidth of the virtual machine into slices once it finishes its execution, and distributes the slices among the co-hosted running virtual machines according to a specific policy. The proposed bandwidth slicing algorithms are emulated in a virtualized networking environment using the Mininet network emulator. The emulation results demonstrated a promising improvement ratio in execution time and energy consumption reaching up to 30%. These results present a call for action for further research into bandwidth slicing and reallocation as a viable complement to other energy-saving techniques for enhancing the energy consumption in cloud data centers.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 112, p. 767-784
Keywords [en]
Bandwidth allocation, Bandwidth Slicing, Cloud Computing, CloudLet, Fog Computing, VM management
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-80352DOI: 10.1016/j.future.2020.06.021ISI: 000567825900022Scopus ID: 2-s2.0-85086830425OAI: oai:DiVA.org:kau-80352DiVA, id: diva2:1470347
Funder
Knowledge FoundationAvailable from: 2020-09-24 Created: 2020-09-24 Last updated: 2024-09-04Bibliographically approved

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Al-Dulaimy, AudayTaheri, Javid

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