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QoS-Constrained Resource Reconfiguration Scheme based on Temporal Quorum Status Estimation in Computational Grids  

Byungsang, Kim
Dong Su, Nam
Bong Hwan, Lee
Publication Information
Journal of KIISE:Information Networking / v.31, no.5, 2004 , pp. 460-468 More about this Journal
Abstract
Quality of Service (QoS)-constrained policy has an advantage to guarantee QoS requirements requested by users. Quorum systems can ensure the consistency and availability of replicated data despite the benign failure of data repositories. We propose a Quorum based resource management scheme, which includes a system resource and network resource, both of which can satisfy the requirements of application QoS. We also propose the resource reconfiguration algorithm based on temporal execution time estimation method. Resource reconfiguration means that reshuffling the current available resource set for maintaining the quality level of the resources. We evaluate the effectiveness of resource reconfiguration mechanism with a Heart Hemodynamics analysis. Our approach shows the increase of the stability of execution environment as well as decrease the completion time compare to the method that is not adapted the resource reconfiguration.
Keywords
Computational Grids; Resource Reconfiguration; temporal Quorum status estimation;
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1 K. Yang, A. Galis, C. Todd 'A Policy-based Active Grid Management Architecture,' Proceedings of 10th IEEE International Conference on Networks (ICOIN02), pp. 243-248, IEEE Press. August 2002   DOI
2 P. Flegkas, P. Trimintzios, G. Pavlou, A. Liotta, Design and Implementation of a Policy-based Resource Management Architecture, Proceedings of IEEE/IFIP Integrated Management Symposium (IM'2003), Colorado Springs, Colorado, USA, pp. 215-229, Kluwer, March 2003
3 Franken, L.J.N. Haverkort, B.R, The performability manager, Network, IEEE performability manager   DOI   ScienceOn
4 A.Leff, J.T.Rayfield, and D.M.Dias, 'Service-Level Agreements and Commercial Grids,' Internet Computing IEEE 2003, pp. 44-5   DOI   ScienceOn
5 I. Cardei, S. Varadarajan, M. Pavan, M. Cardei, M. Min, 'Resource Management for Ad-hoc wireless networks with cluster organization,' Journal of Cluster Computing in the Internet, Kluwer Academic Publishers, Jan. 2004   DOI
6 S. R. Sarukkai and J. C. Yan. 'Event-Based Study of the Effect of Execution Environments on Parallel Program Performance,' Proceedings of the Forth International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOT '96), San Jose CA, February 1996. pages 257-261   DOI
7 Christos G, Cassandras 'Discrete Event Systems, Modeling and Performance analysis' IRWIN
8 Foster, I. and Kesselman, C. (eds.). The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, 1999
9 [Foster, I. and Kesselman, C. The Anatomy of the Grid:Enabling Scalable Virtual Organizations. Intl J. Supercomputer Applications, 2001
10 Frey, J., Foster, I., Livny, M., Tannenbaum, T. and Tuecke, S. Condor-G: A Computation Management Agent for Multi-Institutional Grids, University of Wisconsin Madison, 2001
11 Raman, R, Livny, M., Solomon, M.: Matchmaking: Distributed resource management for high throughput computing. International Symposium on High Performance Distributed Computing (1998)   DOI
12 Abramson, D., Sosic, R, Giddy, J. and Hall, B. Nimrod: A Tool for Performing Parameterized Simulations Using Distributed Workstations. In Proc. 4th IEEE Symp. On High Performance Distributed Computing, 1995
13 R. Buyya, D. Abramson, J. Giddy, and H. Stockinger, 'Economic Models for Resource Management and Scheduling in Grid Computing,' 2002, http://citeseer.nj.nec.corrVbuyya02economic.htmI