Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information

Shen, D; Luo, J; Dong, F; Jin, J; Zhan, J; Shen, J

Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information

Shen, D Luo, J Dong, F Jin, J Zhan, J Shen, J

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Services Computing, 2020, 13, (2), pp. 381-394
Issue Date:: 2020-03-01

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Field	Value	Language
dc.contributor.author	Shen, D
dc.contributor.author	Luo, J
dc.contributor.author	Dong, F
dc.contributor.author	Jin, J
dc.contributor.author	Zhan, J
dc.contributor.author	Shen, J https://orcid.org/0000-0002-9403-7140
dc.date.accessioned	2021-01-06T00:38:24Z
dc.date.available	2021-01-06T00:38:24Z
dc.date.issued	2020-03-01
dc.identifier.citation	IEEE Transactions on Services Computing, 2020, 13, (2), pp. 381-394
dc.identifier.issn	1939-1374
dc.identifier.issn	1939-1374
dc.identifier.uri	http://hdl.handle.net/10453/145102
dc.description.abstract	© 2008-2012 IEEE. Bandwidth allocation to virtual machines (VMs) has a significant impact on the performance of communication-intensive big data applications hosted in VMs. It is crucial to accurately determine how much bandwidth to be reserved for VMs and when to adjust it. Past approaches typically resort to predicting the long-term network demands of applications for bandwidth allocation. However, lacking of prediction accuracy, these methods lead to the unpredictable application performance. Recently, it is conceded that the network demands of applications can only be accurately derived right before each of their execution phases. Hence, it is challenging to timely allocate the bandwidth to VMs with limited information. In this paper, we design and implement AppBag, an Application-aware Bandwidth guarantee framework, which allocates the accurate bandwidth to VMs with one-step-ahead traffic information. We propose an algorithm to allocate the bandwidth to VMs and map them onto feasible hosts. To reduce the overhead when adjusting the allocation, an efficient Lazy Migration (LM) algorithm is proposed with bounded performance. We conduct extensive evaluations using real-world applications, showing that AppBag can handle the bandwidth requests at run-time, while reducing the execution time of applications by 47.3 percent and the global traffic by 36.7 percent, compared to the state-of-the-art methods.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Transactions on Services Computing
dc.relation.isbasedon	10.1109/TSC.2019.2922176
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems
dc.title	Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information
dc.type	Journal Article
utslib.citation.volume	13
utslib.for	0803 Computer Software
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-01-06T00:38:20Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	13
utslib.citation.issue	2

Abstract:

© 2008-2012 IEEE. Bandwidth allocation to virtual machines (VMs) has a significant impact on the performance of communication-intensive big data applications hosted in VMs. It is crucial to accurately determine how much bandwidth to be reserved for VMs and when to adjust it. Past approaches typically resort to predicting the long-term network demands of applications for bandwidth allocation. However, lacking of prediction accuracy, these methods lead to the unpredictable application performance. Recently, it is conceded that the network demands of applications can only be accurately derived right before each of their execution phases. Hence, it is challenging to timely allocate the bandwidth to VMs with limited information. In this paper, we design and implement AppBag, an Application-aware Bandwidth guarantee framework, which allocates the accurate bandwidth to VMs with one-step-ahead traffic information. We propose an algorithm to allocate the bandwidth to VMs and map them onto feasible hosts. To reduce the overhead when adjusting the allocation, an efficient Lazy Migration (LM) algorithm is proposed with bounded performance. We conduct extensive evaluations using real-world applications, showing that AppBag can handle the bandwidth requests at run-time, while reducing the execution time of applications by 47.3 percent and the global traffic by 36.7 percent, compared to the state-of-the-art methods.

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http://hdl.handle.net/10453/145102