Details of Research Outputs

TitleDynamic Consolidation Based on Kth-Order Markov Model for Virtual Machines
Creator
Date Issued2020
Source PublicationEAI/Springer Innovations in Communication and Computing
ISSN2522-8595
Pages21-31
AbstractThe rapid development of cloud computing technology has led to a high level of energy consumption. The central processing unit (CPU) of the data center and other resources often use less than half the rate; therefore, if the work of the virtual machine is focused on part of the server, and the idle server switches to low power mode, the power consumption of the data center can be greatly reduced. Traditional research into virtual machine consolidation is mainly based on the high load threshold of the current host load setting or periodically migrates, and the present study made predictions based on the timing of problems of lower prediction accuracy faced. To solve these problems, we consider the impact of the multi-order Markov model and the CPU state at different times, and propose a new hybrid sequence K Markov model for the next period of time of the host CPU load forecasting. Owing to the large-scale data experiment on the CloudSim simulation platform, the host load forecasting method proposed in this paper is compared with the traditional load detection method to verify that the proposed model has a large reduction in the number of virtual machine migrations and amount of data center energy consumption, and the violation of the service level agreement (SLA) is also at an acceptable level.
KeywordCloud computing Dynamic virtual machine integration Hybrid Markov model
DOI10.1007/978-3-030-17763-8_3
URLView source
Language英语English
Scopus ID2-s2.0-85134329679
Citation statistics
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/12869
CollectionResearch outside affiliated institution
Corresponding AuthorJiang,Na
Affiliation
Zhaotong University,Zhaotong,China
Recommended Citation
GB/T 7714
Jiang,Na. Dynamic Consolidation Based on Kth-Order Markov Model for Virtual Machines[C], 2020: 21-31.
Files in This Item:
There are no files associated with this item.
Related Services
Usage statistics
Google Scholar
Similar articles in Google Scholar
[Jiang,Na]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jiang,Na]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jiang,Na]'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.