Dynamic resource selection heuristics for a non-reserved bidding-based Grid environment

A Grid system is comprised of large sets of heterogeneous and geographically distributed resources that are aggregated as a virtual computing platform for executing large-scale scientific applications. As the number of resources in Grids increases rapidly, selecting appropriate resources for jobs has become a crucial issue. To avoid single point of failure and server overload problems, bidding provides an alternative means of resource selection in distributed systems. However, under the bidding model, the key challenge of resource selection is that there is no global information system to facilitate optimum decision-making; hence requesters can only obtain partial information revealed by resource providers. To address this problem, we propose a set of resource selection heuristics to minimize the turnaround time in a non-reserved bidding-based Grid environment, while considering the level of information about competing jobs revealed by providers. We also present the results of experiments conducted to evaluate the performance of the proposed heuristics.