Cluster-based optimal VM placement using crow search algorithm for cloud data centres Online publication date: Thu, 28-Jan-2021
by Anand Jumnal; S.M. Dilip Kumar
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 16, No. 2/3, 2020
Abstract: The extensive use of computational power from data centres causes huge energy consumption. A good virtual machine (VM) placement strategy would make better consolidation of VMs in a data centre (DC) that reduces energy consumption. However, it is hard to balance hosts in DCs due to the workload fluctuation by application and scaling of VMs. The optimal decision on VM placement and consolidation is an NP-hard problem and many researchers have proposed solutions to tackle this problem but they lack efficient exploitation of the mechanisms. Therefore, this paper proposes a hierarchical cluster-based approach with a meta-heuristic crow search algorithm (CSA) for the optimal selection of hosts to place the VMs and consolidate the maximum number of VMs on a minimum number of hosts. The work is simulated in CloudSim using real workload traces. Experimental results show that proposed work reduces energy consumption, SLA violations and VM migrations while ensuring better resource utilisation.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of High Performance Computing and Networking (IJHPCN):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook