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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bhardwaj, S., Jain, L., Jain, S.: Cloud Computing: A study of Infrastructure As A Service (IAAS). Journal of Engineering and Information Technology 2(1), 60–63 (2010)
Santos, N., Gummadi, K.P., Rodrigues, R.: Towards Trusted Cloud Computing. In: Workshop on Hot Topics in Cloud Computing, USENIX (2009)
Patel, P., Ranabahu, A., Sheth, A.: Service Level Agreement in Cloud Computing. In: Cloud Workshops at OOPSLA 2009 (2009), http://knoesis.wright.edu/aboutus/visitors/summer2009/PatelReport.pdf
Murata, Y.E., Higashida, R., Kobayashi, M., Cybersci, H.: A History-Based Job Scheduling Mechanism for the Vector Computing Cloud. In: 10th Annual Symposium on Applications & the Internet, pp. 125–128. IEEE Press, New York (2010)
You, X., Xu, X., Wan, J., Yu, D.: RAS-M:Resource Allocation Strategy based on Market Mechanism in Cloud Computing. In: 2009 Fourth ChinaGrid Annual Conference, pp. 256–263. IEEE Press, New York (2009)
Assuncao, M.D., Costanzo, A.: Evaluating the Cost-Benefit of Using Cloud Computing to Extend the Capacity of Clusters. In: 18th ACM International Symposium on High Performance Distributed Computing, pp. 141–150. ACM Press, New York (2009)
Lee, Y.C., Wang, C., Zomaya, A.Y., Zhou, B.B.: Profit-driven Service Request Scheduling in Clouds. In: 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 15–24. IEEE Press, New York (2010)
Wu, L., Buyya, R.: Service Level Agreement (SLA) in Utility Computing Systems. Thechnical report, CLOUDS-TR-2010-5, Cloud Computing and Distributed Systems Laboratory (2010)
Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)
OWL Web Ontology Language Reference, W3C Recommendation, http://www.w3.org/TR/owl-ref/
SWRL: A Semantic Web Rule Language Combining OWL and RuleML, W3C Recommendation, http://www.w3.org/Submission/SWRL/
Ziegler, B.P., Sarjoughian, H.S., Park, S.W., Lee, J.S., Cho, Y.K., Nutaro, J.J.: DEVS modeling and Simulation: a new layer of middleware. In: 3rd Annual International Workshop on Active Middleware Services, pp. 22–31. IEEE Press, New York (2001)
Protégé, http://protege.stanford.edu/
Jang, M.S., Sohn, J.C.: Bossam: An Extended Rule Engine for OWL Inferencing. In: Antoniou, G., Boley, H. (eds.) RuleML 2004. LNCS, vol. 3323, pp. 128–138. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ma, Y.B., Jang, S.H., Lee, J.S. (2011). Ontology-Based Resource Management for Cloud Computing. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20042-7_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-20042-7_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20041-0
Online ISBN: 978-3-642-20042-7
eBook Packages: Computer ScienceComputer Science (R0)