Paper Info
Title
Supporting Load-Balanced Virtual Machine Placement for Cloud Infrastructure as a Service.
Abstract
Infrastructure-as-a-service (IaaS) is an important type of cloud service. It integrates conventional computing resources, network resources, storage resources and related software packages into an on-demand network service, which provide virtual resources and machines to the users instead. Therefore, it is important to use a good VM placement mechanism that achieves good performance in an IaaS platform. For example, while allocating resources to a set of virtual machines (VMs), load balance is an important technique to avoid resource usage surge and thus can provide good quality of services to users. In this paper, we present a new VM placement mechanism based on resource usage prediction. The mechanism is implemented on a cloud platform, namely SAMEVED-Stack. The SAMEVED-Stack is a non-commercial cloud platform that supports high-level operations for virtual cluster/datacenter management. It is derived from OpenStack, and designed for supporting on-line network and computer security experiments. Our preliminary results show that, the proposed VM placement strategy outperforms three popular VM placement strategies, the Best-Fit, the First-Fit, and the max-free-memory-fit.
Year
DOI
Venue
2014
10.3233/978-1-61499-484-8-1396
Frontiers in Artificial Intelligence and Applications
Keywords
Field
DocType
Cloud Computing,OpenStack,Resource Allocation,Load Balancing
Virtual machine,Load balancing (computing),Computer science,Computer network,Distributed computing,Cloud computing,Converged infrastructure
Conference
Volume
ISSN
Citations 
274
0922-6389
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Wei-Jen Wang115013.65
Shao-Jui Chen242.89
Jui-Hao Yang300.34
Tzu-Ming Chan400.34