Ontology-based resource management for cloud computing

Authors:
Yong Beom Ma;Sung Ho Jang;Jong Sik Lee
Affiliations:
School of Information Engineering, Inha University, Incheon, South Korea;School of Information Engineering, Inha University, Incheon, South Korea;School of Information Engineering, Inha University, Incheon, South Korea
Venue:
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Year:
2011

Citing 7
Cited 0

A translation approach to portable ontology specifications

Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Devs Modeling And Simulation: A New Layer Of Middleware

AMS '01 Proceedings of the Third Annual International Workshop on Active Middleware Services
Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters

Proceedings of the 18th ACM international symposium on High performance distributed computing
RAS-M: Resource Allocation Strategy Based on Market Mechanism in Cloud Computing

CHINAGRID '09 Proceedings of the 2009 Fourth ChinaGrid Annual Conference
Profit-Driven Service Request Scheduling in Clouds

CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Towards trusted cloud computing

HotCloud'09 Proceedings of the 2009 conference on Hot topics in cloud computing
A History-Based Job Scheduling Mechanism for the Vector Computing Cloud

SAINT '10 Proceedings of the 2010 10th IEEE/IPSJ International Symposium on Applications and the Internet

Quantified Score

Hi-index	0.00

Visualization

Abstract

Resource management is a challenging issue in cloud computing. This paper aims to allocate requested jobs to cloud resources suitable for cloud user requirements. To achieve the aim, this paper proposes an ontology-based job allocation algorithm for cloud computing to perform inferences based on semantic meanings. We extract resource candidates depending on user requirements and allocate a job to the most suitable candidate for an agreed Service Level Agreement (SLA). The cloud ontology allows the proposed system to define concepts and describe their relations. Hence, we can process complicated queries for searching cloud resources. To evaluate performance of our system, we conducted some experiments compared with the existing resource management algorithms. Experimental results verify that the ontology-based resource management system improves the efficiency of resource management for cloud computing.