Assuring predictable resources (processors, memory, storage) for applications running on the Grid is a critical factor for the success of the Grid for solving real-life problems. We extend the Globus Resource Management Architecture to provide metascheduling, co-scheduling and advance co-reservation of resources, and compare the proposed architecture with existing metascheduling solutions.
Get full access to this article
View all access options for this article.
References
1.
Allcock, B., Bester, J., Bresnahan, J., Chervenak, A.L., Foster, I., Kesselman, C., Meder, S., Nefedova, V., Quesnel, D., and Tuecke, S. 2002. Data management and transfer in high-performance computational grid environments . Parallel Computing, 28(5): 749–771 .
2.
Bester, J., Foster, I., Kesselman, C., Tedesco, J., and Tuecke, S. 1999. GASS: A data movement and access service for wide area computing systems. In Proceedings of the Sixth Workshop on Input/Output in Parallel and Distributed Systems, pp. 78–88, Atlanta, GA, ACM Press .
3.
Czajkowski, K., Foster, I., Karonis, N., Kesselman, C., Martin, S., Smith, W., and Tuecke, S. 1998. A resource management architecture for metacomputing systems. In D.G. Feitelson and L. Rudolph, editors, Job Scheduling Strategies for Parallel Processing, Vol. 1459, Lecture Notes in Computer Science, pp. 62–82, Springer-Verlag, Berlin .
4.
Czajkowski, K., Foster, I., and Kesselman, C. 1999. Resource co-allocation in computational grids. In Proceedings of the Eighth IEEE International Symposium on High Performance Distributed Computing (HPDC-8), pp. 219–228.
5.
Foster, I., and Kesselman, C. 1997. Globus: A metacomputing infrastructure toolkit . International Journal of Supercomputer Applications and High Performance Computing, 11(2): 115–128 .
6.
Foster, I., Kesselman, C., and Tuecke, S. 2001. The anatomy of the Grid: enabling scalable virtual organizations . High Performance Computing Applications, 15(3): 200–222 .
7.
Hamscher, V., Schwiegelshohn, U., Streit, A., and Yahyapour, R. 2000. Evaluation of job-scheduling strategies for grid computing. Number 1971 in Lecture Notes in Computer Science, pp. 191–202, Springer-Verlag, Berlin .
8.
Harrison, K., Mato, P., Soroko, A., and Tull, C. 2003. Ganga: a user-grid interface for ATLAS and LHCb . In Conference for Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, CA, March.
9.
Henderson, R.L. 1995. Job scheduling under the Portable Batch System. In D.G. Feitelson and L. Rudolph, editors, Job Scheduling Startegies for Paralell Processing, Vol. 949 Lecture Notes in Compuater Science, pp. 279–294, Springer-Verlag, Berlin .
10.
Lumb, I. 2003. Scheduling attributes and platform LSF. In J. Weglarz, J. Nabrzyski, J. Schopf, and M. Stroinski, editors, Grid Resource Management, Kluwer Academic, Dordrecht .
11.
Mateescu, G. 2003. A dynamic space sharing method for resource management. In R.D. Kent and T.W. Sands, editors, High Performance Computing Systems and Applications, Vol. 727, Kluwer International Series in Engineering And Computer Science, pp. 167–176, Kluwer Academic, Dordrecht .
12.
Ramamoorthi, R., Rifkin, A., Dimitrov, B., and Chandy, K.M. 1997. A general resource reservation framework for scientific computing. In Y. Ishikawa, R.R. Oldehoeft, J.V.W. Reynders, and M. Tholburn, editors, Lecture Notes in Computer Science, Vol. 1343, pp. 283–290, Springer-Verlag, Berlin .
13.
Schwiegelshohn, U., and Yahyapour, R. October 2002. Grid scheduling architecture. Global Grid Forum, http://www.ggf.org.
14.
Subramani, V., Kettimuthu, R., Srinivasan, S., and Sadayappan, P. 2002. Distributed job scheduling on computational grids using multiple simultaneous requests . In Proceedings of the 11th IEEE Symposium on High Performance Distributed Computing (HPDC 2002), July, pp. 354–361 , Los Alamitos, CA, IEEE.
15.
Wolski, R. 1997. Forecasting network performance to support dynamic scheduling using the network weather service . In 6th IEEE Symposium on High Performance Distributed Computing, pp. 316–325 .
16.
Zhou, S. 1992. LSF: Load sharing in large-scale heterogeneous distributed systems . In Proceedings of the Workshop on Cluster Computing, Tallahassee, FL, December.
