Paper Info
Title
An autonomic approach for resource provisioning of cloud services.
Abstract
Recently, there has been a significant increase in the use of cloud-based services that are offered in software as a service (SaaS) models by SaaS providers, and irregular access of different users to these cloud services leads to fluctuations in the demand workload. It is difficult to determine the suitable amount of resources required to run cloud services in response to the varying workloads, and this may lead to undesirable states of over-provisioning and under-provisioning. In this paper, we address improvements to resource provisioning for cloud services by proposing an autonomic resource provisioning approach that is based on the concept of the control monitor-analyze-plan-execute (MAPE) loop, and we design a resource provisioning framework for cloud environments. The experimental results show that the proposed approach reduces the total cost by up to 35 %, the number of service level agreement (SLA) violations by up to 40 %, and increases the resource utilization by up to 25 % compared with the other approaches.
Year
DOI
Venue
2016
10.1007/s10586-016-0574-9
Cluster Computing
Keywords
Field
DocType
Cloud computing,Cloud services,Resource provisioning,MAPE loop,Learning automata
Services computing,Learning automata,Workload,Computer science,Service-level agreement,Computer network,Real-time computing,Provisioning,Software as a service,Total cost,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
19
3
1386-7857
Citations 
PageRank 
References 
20
0.72
41
Authors
3
Name
Order
Citations
PageRank
Mostafa Ghobaei Arani118916.41
Sam Jabbehdari2916.87
Mohammad Ali Pourmina31079.75