Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30172
Proffering a Brand New Methodology to Resource Discovery in Grid based on Economic Criteria Using Learning Automata

Authors: Ali Sarhadi, Mohammad Reza Meybodi, Ali Yousefi

Abstract:

Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.

Keywords: Resource discovery, learning automata, neural network, economic policy

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334768

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1122

References:


[1] I. Foster, C. Kesselman and S. Tuecke, "The anatomy of the Grid: Enabling scalable virtual organizations", International Journal of Supercomputer Applications, 2001.
[2] Viktors Berstis, "Fundamentals of Grid Computing", IBM Redbook series, November 2002, http://ibm.com/redbooks.
[3] R. Buyya, D. Abramson, and J. Giddy, "A Case for Economy Grid Architecture for Service-Oriented Grid Computing", Proceedings of the 10th IEEE International Heterogeneous Computing Workshop, April 2001.
[4] R. Buyya, D. Abramson, J. Giddy, and H. Stockinger, "Economic Models for Resource Management and Scheduling in Grid Computing", The Journal of Concurrency and Computation: Practice and Experience, May 2002.
[5] M. Murshed, R. Buyya, and D. Abramson, "GridSim: A Portable and Scalable Toolkit for Modeling and Simulation of Application Scheduling for Parallel and Distributed Computing", Technical Report, Monash University, Oct. 2001. Available at: http://www.buyya.com/gridsim/.
[6] K. Narendra and M. A. L. Thathachar, Learning Automata: An Introduction, Prentice Hall, Englewood Cliffs, New Jersey, 1989.
[7] S. Lalis and A. Karipidis, "An Open Market-Based Framework for Distributed Computing over the Internet", Proceedings of the First IEEE/ACM International Workshop on Grid Computing (GRID 2000), Bangalore, India, Springer Verlag Press, Germany, December 2000.
[8] Maxine Brown, Thomas DeFanti, Michael McRobbie, Alan Verlo, Dana Plepys, Donald McMullen, Karen Adams, Jason Leigh, Andrew Johnson, Ian Foster, Carl Kesselman, Andrew Schmidt, Steven Goldstein: The International Grid (iGrid): Empowering Global Research Community Networking Using High Performance International Internet Services. Proceedings of INET, 2003, pp. 3-9.
[9] Puppin, D., Moncelli S., Baraglia, R., Tonellotto, N.,Silvestri, F.: A peer-to-peer information service for the grid. In: Proceedings of the GridNets 2004 Workshop, San Jos'e, CA (2004)
[10] K. Narendra and M. A. L. Thathachar, Learning Automata: An Introduction, Prentice Hall, Englewood Cliffs, New Jersey, 1989.
[11] K. Najim and A. S. Poznyak, Learning Automata: Theory and Application, Elsevier Science Ltd., Tarrytown, NY, 1994.
[12] A. Galstyan, K. Czajkowski, and K. Lerman, "Resource allocation in the grid using reinforcement learning", Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'04), pp. 1314-1315, 2004.
[13] Carsten Peterson and Thorsteinn Rognvaldsson, An Introduction to Artificial Neural Networks, LU TP 91-23, September 1991 (Lectures given at the 1991 Cern School of Computing, Sweden)
[14] R. Buyya and M. Murshed, "GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing", Journal of Concurrency and Computation: Practice and Experience, pp. 1-32, May 2002.
[15] R. Buyya, D. Abramson, J. Giddy, and H. Stockinger, "Economic Models for Resource Management and Scheduling in Grid Computing", The Journal of Concurrency and Computation: Practice and Experience, May 2002.
[16] Rummelhart, D. E.; Hinton, G. E.; Williams, R. J., (2004).Learning representations by back-propagation errors. ature, 323, 533-536.
[17] S. Castano, A. Ferrara, S. Montanelli and G. Racca, "Matching Techniques for Resource Discovery in Distributed Systems Using Heterogeneous Ontology Descriptions". Proc. Int. Conf. on Information Technology:Coding and Computing (ITCC-04), vol. 1, pp. 360-366, 2004.