Paper Info
Title
Automatic Resource Provisioning: A Machine Learning Based Proactive Approach
Abstract
This paper concerns dynamic provisioning of cloud resources performed by an intermediary enterprise that provides a private cloud (also referred to as a virtual private cloud) for a single client enterprise using resources acquired on demand from a public cloud. A new proactive technique for auto-scaling of resources that changes the number of resources for the private cloud dynamically based on system load is proposed. The technique that supports both on-demand and advance reservation requests uses machine learning to predict future workload based on past workload. Experimental results demonstrate that the proposed technique can effectively lead to a profit for the intermediary enterprise as well as a reduction of cost for the client enterprise.
Year
DOI
Venue
2014
10.1109/CloudCom.2014.147
Cloud Computing Technology and Science
Keywords
Field
DocType
business data processing,cloud computing,learning (artificial intelligence),resource allocation,advance reservation requests,automatic resource provisioning,client enterprise,cloud resources,dynamic provisioning,machine learning based proactive approach,on-demand reservation requests,private cloud,public cloud,resources auto-scaling,single client enterprise,auto-scaling,dynamic resource provisioning,resource allocation,resource management on clouds,scheduling with SLAs
Reservation,Computer science,Real-time computing,Artificial intelligence,Distributed computing,Resource management,Workload,Support vector machine,Provisioning,Resource allocation,Enterprise private network,Machine learning,Cloud computing
Conference
ISSN
Citations 
PageRank 
2330-2194
7
0.52
References 
Authors
7
4
Name
Order
Citations
PageRank
Anshuman Biswas1212.84
Shikharesh Majumdar243575.95
Biswajit Nandy319221.75
El-Haraki, A.4183.55