Paper Info
Title
Energy and quality of service-aware virtual machine consolidation in a cloud data center
Abstract
The large-scale virtualized Cloud data centers consume huge amount of electrical energy leading to high operational costs and emission of greenhouse gases. Virtual machine (VM) consolidation has been found to be a promising approach to improve resource utilization and reduce energy consumption of the data center. However, aggressive consolidation of VMs tends to increase the number of VM migrations and leads to over-utilization of hosts. This in turn affects the quality of service (QoS) of the applications running in the VMs. Thus, reduction in energy consumption and at the same time ensuring proper QoS to the Cloud users are one of the major challenges among the researchers. In this paper, we have proposed an energy efficient and QoS-aware VM consolidation technique in order to address this problem. We have used Markov chain-based prediction approach to identify the over-utilized and under-utilized hosts in the data center. We have also proposed an efficient VM selection and placement policy based on linear weighted sum approach to migrate the VMs from over-utilized and under-utilized hosts considering both energy and QoS. Extensive simulations using real-world traces and comparison with state-of-art strategies show that our VM consolidation approach substantially reduces energy consumption within a data center while delivering suitable QoS.
Year
DOI
Venue
2020
10.1007/s11227-020-03203-3
The Journal of Supercomputing
Keywords
DocType
Volume
Cloud computing, Energy, Quality of service, Virtual machine consolidation, Virtual machine placement, Virtual machine selection
Journal
76
Issue
ISSN
Citations 
11
0920-8542
4
PageRank 
References 
Authors
0.40
0
4
Name
Order
Citations
PageRank
Anurina Tarafdar140.74
Mukta Debnath240.40
Sunirmal Khatua312015.00
Rajib K. Das4358.94