Multiple Grid Environments Research Articles

On Construction of a Multi-Grid Resource Selection Strategy on Grids

Grid computing is now in widespread use, integrating geographical computing resources across multiple virtual organizations to achieve high performance computing. A single grid does not often provide a vast resource because virtual organizations have inadequate computing resource restrictions for management on an organizational scale. This paper presents a new grid architecture named Multi-Grid, which integrates multiple computational grids from different virtual organizations. This study builds a resource broker on multiple grid environments, integrating a number of single grids from different virtual organizations without the limit of organizations. The purpose of the multiple-grid resource is to avoid wasting resources. In addition, this study proposes a Multi-Grid Resource Selection Strategy (MRGSS) for the resource broker to better allocate resources before submitting jobs, to avoid network congestion that consequently causes a decrease in performance.

Performance analysis of allocation policies for interGrid resource provisioning

Several Grids have been established and used for varying science applications during the last years. Most of these Grids, however, work in isolation and with different utilisation levels. Previous work has introduced an architecture and a mechanism to enable resource sharing amongst Grids. It has demonstrated that there can be benefits for a Grid to offload requests or provide spare resources to another Grid. In this work, we address the problem of resource provisioning to Grid applications in multiple-Grid environments. The provisioning is carried out based on availability information obtained from queueing-based resource management systems deployed at the provider sites which are the participants of the Grids. We evaluate the performance of different allocation policies. In contrast to existing work on load sharing across Grids, the policies described here take into account the local load of resource providers, imprecise availability information and the compensation of providers for the resources offered to the Grid. In addition, we evaluate these policies along with a mechanism that allows resource sharing amongst Grids. Experimental results obtained through simulation show that the mechanism and policies are effective in redirecting requests thus improving the applications’ average weighted response time.