Divisible Load Scheduling in Mobile Grid based on Stackelberg Pricing Game

TL;DR

This paper proposes a Stackelberg Pricing Game-based algorithm for scheduling divisible loads in mobile grid systems, optimizing resource sharing and reducing task completion time through strategic pricing.

Contribution

It introduces a novel Stackelberg Pricing Game model for mobile grid load scheduling, enhancing resource utilization and minimizing task makespan.

Findings

The algorithm significantly reduces task makespan in simulations.

The Stackelberg Pricing Game effectively incentivizes resource providers.

Performance improvements are validated through system simulations.

Abstract

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.