Online Metatask Scheduling Heuristics for a Bidding-based Distributed System

In the last decade, the evolution of distributed computing has shifted from cluster computing to Grid computing. Although bidding provides a useful means of resource allocation for this novel computing paradigm, there exist two challenges to scheduling metatasks in bidding-based Grid systems. (1) The scheduling algorithm has to avert collisions between the jobs of a metatask, as well as prevent contention between the metatasks submitted by different requesters. (2) There is no global information system to facilitate optimum decision-making; hence, requesters are only aware of partial information released by resource providers. To address these challenges, we propose a set of scheduling heuristics to minimize the makespan of each metatask, while simultaneously considering the level of information about competing metatasks revealed by providers. We also present the results of experiments conducted to evaluate the performance of the proposed heuristics.