UM  > Faculty of Science and Technology
Residential Collegefalse
Status已發表Published
Energy efficient VM scheduling strategies for HPC workloads in cloud data centers
Chandio,Aftab Ahmed1,2; Tziritas,Nikos1; Chandio,Muhammad Saleem2; Xu,Cheng Zhong1,3,4
2019-12
Source PublicationSustainable Computing: Informatics and Systems
ISSN2210-5379
Volume24
Abstract

In virtualized environments, virtual machine (VM) scheduling strategies incorporated with energy efficient techniques are needed to reduce the operational cost of the system while delivering high Quality of Service (QoS). It is widely accepted that the cost of the energy consumption in the environment is a dominant part of the owner's budget. However, when considering energy efficiency, VM scheduling decisions become more constrained, leading in the violation of job deadlines and hence compromising QoS. This paper studies energy efficient VM scheduling strategies in virtualized environments to minimize the queue time and makespan under the fulfillment of SLA requirements (i.e., deadline). Specifically, six energy efficient VM scheduling strategies are investigated incorporated with the dynamic voltage and frequency scaling (DVFS) power management technique. They consist of user-oriented and system-oriented policies. The strategies are extensively simulated and compared with three power management governing methods provided at hypervisor level (i.e., userspec, ondemand, and performance). To conduct simulation experiments, we employ real-world high performance computing (HPC) workloads collected from a production data center. For comparison and evaluation, we analyze the: (a) energy consumption, (b) runtime, (c) queue time, (d) makespan, and (e) slowdown ratio. Lastly, we highlight the strengths and weaknesses of the VM scheduling strategies that can help to choose the most appropriate VM scheduling strategy for a given scenario.

KeywordCloud Computing Dvfs Energy Efficiency Hpc Cloud Hypervisor Power Management Schemes Vm Scheduling
DOI10.1016/j.suscom.2019.100352
URLView the original
Language英語English
WOS IDWOS:000501803900001
Scopus ID2-s2.0-85072762971
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorChandio,Aftab Ahmed
Affiliation1.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,518055,China
2.Institute of Mathematics and Computer Science,University of Sindh,Jamshoro,70680,Pakistan
3.Department of Electrical and Computer Engineering,Wayne State University,Detroit,48202,United States
4.Department of Computer Science State Key Lab. of IoT for Smart City University of Macau,Macao SAR,China
Recommended Citation
GB/T 7714
Chandio,Aftab Ahmed,Tziritas,Nikos,Chandio,Muhammad Saleem,et al. Energy efficient VM scheduling strategies for HPC workloads in cloud data centers[J]. Sustainable Computing: Informatics and Systems, 2019, 24.
APA Chandio,Aftab Ahmed., Tziritas,Nikos., Chandio,Muhammad Saleem., & Xu,Cheng Zhong (2019). Energy efficient VM scheduling strategies for HPC workloads in cloud data centers. Sustainable Computing: Informatics and Systems, 24.
MLA Chandio,Aftab Ahmed,et al."Energy efficient VM scheduling strategies for HPC workloads in cloud data centers".Sustainable Computing: Informatics and Systems 24(2019).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chandio,Aftab Ahmed]'s Articles
[Tziritas,Nikos]'s Articles
[]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chandio,Aftab Ahmed]'s Articles
[Tziritas,Nikos]'s Articles
[Chandio,Muhamma...]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chandio,Aftab Ahmed]'s Articles
[Tziritas,Nikos]'s Articles
[Chandio,Muhamma...]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.