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.

Additional Metadata
Keywords Distributed systems, Dynamic adaptation, File transfers, Grid computing, High performance computing
Persistent URL dx.doi.org/10.1007/978-3-540-88871-0_56
Citation
Ahmad, I. (Imran), & Majumdar, S. (2008). A two level approach for managing resource and data intensive tasks in grids. doi:10.1007/978-3-540-88871-0_56