| Distributed systems such as Grids, aim to enable the sharing, selection, and aggregation of a wide variety of resources that are geographically distributed and often owned by different organizations. These resources collaborate for performing complex tasks. Without efficient resource management, the benefits of a Grid system cannot be realized, especially for large-scale computational and data intensive tasks. The efficient management of distributed resources to perform a complex task is important. In a Grid, a resource management system is responsible for managing the available resources for a given task to be performed. This thesis proposes an effective resource management system called BiLeG, which can be used for performing resource intensive tasks in a Grid computing environment. This thesis focuses on the problem of allocating resources for a group of a particular type of resource intensive tasks termed Processable Bulk Data Transfer (PBDT) tasks. A PBDT task involves the transfer of a very large volume of data that has to be processed in some way before it can be used at a remote set of sink nodes. In BiLeG, the resource management system is bifurcated into separate upper and lower decision making levels and separate responsibilities are assigned to each decision making level. The upper decision making level of BiLeG, called the Task Resource Pool Selector (TRPS), is concerned with selection of a resource-pool for the given task. The lower decision making level, called Resource Allocator (RA) is responsible for allocating resources out of the resource-pool chosen by TRPS. At TRPS, a policy determines the way the resource-pool is chosen for each of the tasks. At RA, an algorithm which determines the allocation of the resources from its resource-pool for the task selected by TRPS is deployed. Note that the resource allocation problem considered in this research focuses on achieving a good balance between multiple performance metrics. Although existing research has addressed various issues in resource allocation, none of the existing works has dealt with resource allocation for PBDT tasks addressing multiple performance metrics that this research focuses on. |
