Abstract
The intelligent agent works powerful jobs for handling system complexity and making systems more modular. Especially a reasoning agent is effective on organizing for decision-making process of systems. This paper introduces an Ontology-based Intelligent Agent for a Grid Resource Management System (OIAGRMS), which uses ontology reasoning to select a suitable resource supplier, is proposed. This paper focuses on effective grid resource management and the improvement of resource utilization through transaction management for the OIAGRMS. For performance evaluation with accuracy and reliability, the OIAGRMS is compared with the Prediction-based Agent for Grid Resource Management System(PAGRMS) and the Random-based Agent for Grid Resource Management System(RAGRMS). The OIAGRMS recorded over 90 percents trade success, but the PAGRMS and RAGRMS recorded less than a 90 percents trade success. In comparing of resource utilization rate, maximum deviation, standard deviation, the OIAGRMS were about 9.4 and 9.8 percents but the PAGRMS are about 22.9 and 16.3 percents, the RAGRMS were about 61.6 and 21.7 percents. The empirical results demonstrate the usefulness and improvement utilization with stable performances of the intelligent agent base on ontology reasoning in grid environment.
This is a preview of subscription content, log in via an institution to check access.
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
Wooldridge, M., Jennings, N.R.: Intelligent Agents: Theory and Practice. The Knowledge Engineering Review 10(2), 115–152 (1995)
Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a Future Computing Infrastructure. Morgan Kaufmann Publishers, USA (1999)
Xing, W., Dikaiakos, M.D., Sakellariou, R., Orlando, S., Laforenza, D.: Design and development of a core grid ontology. In: Gorlatch, Danelutto, M. (eds.) CoreGRID Integration Workshop, Italy, pp. 21–31 (2005)
Buyya, R., Chapin, S., DiNucci, D.: Architectural Models for Resource Management in the Grid. Grid Computing GIRD 2000. In: First IEEE/ACM International Workshop, pp. 20–33 (2000)
Chapin, S., Clement, M., Snell, Q.: A Grid Resource Management Architecture, Grid Forum Scheduling Working Group (1999)
Buyya, R., Abramson, D., Giddy, J.: A Case for Economy Grid Architecture for Service Oriented Grid Computing. In: Proceedings of International Parallel and Distributed Processing Symposium: Heterogeneous Computing Workshop (2001)
Cho, K.C., Kim, T.Y., Lee, J.S.: User Demand Prediction-based Resource Management Model in Grid Computing Environment. In: ICHIT 2008, Korea, pp. 627–632 (2008)
Thompson, C.: Characterizing the Agent Grid, Technical Report, Object Services and Consulting, Inc., http://www.objs.com/agility/tech-reports/9812-grid.html
Tierney, B., Johnston, W., Lee, J., Thompson, M.: A data intensive distributed computing architecture for grid applications. Future Generation Computer Systems 16(5), 473–481 (2000)
Rana, O.F., Walker, D.W.: The agent grid: agent-based resource integration in PSEs. In: Proceedings of 16th IMACS World Congress on Scientific Computation, Applied Mathematics and Simulation (2000)
Shen, W., Li, Y., Ghenniwa, H., Wang, C.: Adaptive negotiation for agent-based grid computing. In: Proceedings of AAMAS Workshop on Agentcities Challenges in Open Agent Environments, pp. 32–36 (2002)
Horridge, M., Knublach, H., Rector, A., Stevens, R., Wroe, C.: A practical guide to building OWL ontologies using the Protégé-OWL plugin and CO-ODE tools. University of Manchester (2004)
Fikes, R., Hayes, P., Horrocks, I.: Owl-ql: A language for deductive query answering on the semantic web, Technical Report KSL 03-14, Stanford University (2003)
Roure, D.D.: A brief history of the semantic grid. In: Semantic Grid: The Convergence of Technologies, number 05271, Dagstuhl Seminar Proceedings. IBFI, Dagstuhl, Germany (2005)
McGuinness, D.L., Harmelen, F.V.: OWL Web Ontology Language Overview, W3C Proposed Recommendation (2003), http://www.w3.org/TR/2003/PR-owl-features-20031215/
Brickley, D., Guha, R.V.: FDF Vocabulary Description Language 1.0:RDF Scheman, W2C Working Draft (2003)
Protégé, http://protege.stanford.edu/
Zeigler, B.P., et al.: The DEVS Environment for High-Performance Modeling and Simulation. IEEE C S & E 4(3), 61–71 (1997)
Kalpakam, S., Arivarignan, G.: Inventory System with Random Supply Quantity, OR Spektrum, pp. 139–145 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cho, K.C., Noh, C.H., Lee, J.S. (2009). Ontology-Based Intelligent Agent for Grid Resource Management. In: Nguyen, N.T., Kowalczyk, R., Chen, SM. (eds) Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. ICCCI 2009. Lecture Notes in Computer Science(), vol 5796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04441-0_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-04441-0_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04440-3
Online ISBN: 978-3-642-04441-0
eBook Packages: Computer ScienceComputer Science (R0)