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Virtual Machine Consolidation with Minimization of Migration Thrashing for Cloud Data Centers
- Source :
- Mathematical Problems in Engineering, Vol 2020 (2020)
- Publication Year :
- 2020
- Publisher :
- Hindawi Limited, 2020.
-
Abstract
- Cloud data centers consume huge amount of electrical energy bringing about in high operating costs and carbon dioxide emissions. Virtual machine (VM) consolidation utilizes live migration of virtual machines (VMs) to transfer a VM among physical servers in order to improve the utilization of resources and energy efficiency in cloud data centers. Most of the current VM consolidation approaches tend to aggressive-migrate for some types of applications such as large capacity application such as speech recognition, image processing, and decision support systems. These approaches generate a high migration thrashing because VMs are consolidated to servers according to VM’s instant resource usage without considering their overall and long-term utilization. The proposed approach, dynamic consolidation with minimization of migration thrashing (DCMMT) which prioritizes VM with high capacity, significantly reduces migration thrashing and the number of migrations to ensure service-level agreement (SLA) since it keeps VMs likely to suffer from migration thrashing in the same physical servers instead of migrating. We have performed experiments using real workload traces compared to existing aggressive-migration-based solutions; through simulations, we show that our approach improves migration thrashing metric by about 28%, number of migrations metric by about 21%, and SLAV metric by about 19%.
- Subjects :
- Decision support system
Article Subject
Computer science
General Mathematics
Distributed computing
General Engineering
Thrashing
020206 networking & telecommunications
Workload
02 engineering and technology
Engineering (General). Civil engineering (General)
computer.software_genre
Virtual machine
Server
Metric (mathematics)
QA1-939
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Minification
TA1-2040
computer
Mathematics
Live migration
Efficient energy use
Subjects
Details
- ISSN :
- 15635147 and 1024123X
- Volume :
- 2020
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....a70ec4e6d07ab957125674f7cb5f3db2