A Sequential Game-Based Resource Allocation Strategy in Grid Environment

In grid environment, resource load prediction is one of the most important problems in resource allocation optimization. But load status is difficult to estimate accurately due to the dynamic nature and heterogeneity of grid resource. In response to this issue, a resource allocation strategy that uses sequential game method to predict resource load for time optimization in a proportional resource sharing environment is proposed. The problem of multiple users bidding to compete for a common computational resource is formulated as a multi-player dynamic game. Through finding the Nash equilibrium solution of the multi-player dynamic game, resource load is predicted. Using this load information, a set of user optimal bids is produced to partition resource capacity according to proportional sharing mechanism. The experiments are performed based on the GridSim toolkits and the results show that the proposed strategy could generate reasonable user bids, reduce resource processing time, hence overcome the deficiency of Bredin’s strategy, which is not concerned with resource load variation. The conclusion indicates that employing sequential game method for load prediction is feasible in grid resource allocation and adapts better to the dynamic nature of heterogeneous resource in grid environment.