A Two Level Approach for Managing Resource and Data Intensive Tasks in Grids
In recent years, Grid computing has emerged as an attractive platform to tackle various large-scale problems, especially in the field of science and engineering. Scheduling Grid resources involves a number of challenging issues, mainly due to the distributed and dynamic nature of the Grids. This paper focuses on the resource allocation for a particular type of resource intensive tasks called Processable Bulk Data Transfer (PBDT) tasks in a Grid environment. The defining trait of a PBDT task is a large raw data-file at a source node that needs to be processed in some way before it can be used at a set of sink nodes. Our scheduling approach uses a Bi-level decision-making architecture. This paper analyzes the performance of the proposed architecture at various workload conditions. This architecture can be extended for other types of tasks using the concepts presented.
Keywordsdistributed systems dynamic adaptation high performance computing file transfers grid computing
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- 2.Abbas, A.: Grid Computing: A Practical Guide to Technology and Applications. Charles River Media (2004)Google Scholar
- 3.Ahmad, I., Majumdar, S.: An adaptive high performance architecture for processable bulk data transfers on a Grid. In: 2nd International Conference on Broadband Networks (Broadnets), October 3-7, pp. 1482–1491. IEEE, Boston (2005)Google Scholar
- 5.Allcock, B., Chervenak, A., Foster, I., Kesselman, C., Livny, M.: Data Grid tools: enabling science on big distributed data. Journal of Physics: Conference Series 16(1), 571–575 (2005)Google Scholar
- 6.Bunn, J., Newman, H.: Data-intensive Grids for high energy physics. In: Berman, G., Hey, E. (eds.) Grid Computing: Making the Global Infrastructure a Reality. John Wiley & Sons, New York (2003)Google Scholar
- 8.Foster, I., Kesselman, C.: The Grid: Blueprint for a Future Computing Infrastructure. Morgan Kaufmann Publishers, USA (1999)Google Scholar
- 9.Foster, I., Kesselman, C., Lee, C., Lindell, B., Nahrstedt, K., Roy, A.: A distributed resource management architecture that supports advance reservations and co-allocation. In: Anonymous Proceedings of IWQoS 1999 - Seventh International Workshop on Quality of Service, May 31-June 4, pp. 27–36. IEEE, London (1999)Google Scholar
- 10.Elayeb, M.: Efficient Data Scheduling For Real-Time Large Scale Data Intensive Distributed Applications (Masters Dissertation, The Ohio State University)Google Scholar
- 11.Paranhos, D., Cirne, W., Brasileiro, F.: Trading Cycles for Information: Using Replication to Schedule Bag-of-Tasks Applications on Computational Grids. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003, vol. 2790, pp. 150–169. Springer, Heidelberg (2003)Google Scholar