Nowadays, it has become feasible to use mobile nodes as contributing entities in computing systems. In this paper, we consider a computational grid in which the mobile devices can share their idle resources to realize parallel processing. The overall computing task can be arbitrarily partitioned into multiple subtasks to be distributed to mobile resource providers (RPs). In this process, the computation load scheduling problem is highlighted.

Based on the optimization objective, i.e., minimizing the task makespan, a buyer-seller model in which the task sponsor can inspire the SPs to share their computing resources by paying certain profits, is proposed. The Stackelberg Pricing Game (SPG) is employed to obtain the optimal price and shared resource amount of each SP. Finally, we evaluate the performance of the proposed algorithm by system simulation and the results indicate that the SPG-based load scheduling algorithm can significantly improve the time gain in mobile grid systems.