A game theory based pricing strategy for job allocation in mobile grids

Abstract

Summary form only given. This article realizes the vision of mobile grid computing by proposing a fair pricing strategy and an optimal, static job allocation scheme. Mobile devices has not yet been integrated into grid computing platforms mainly due to their inherent limitations in processing and storage capacity, power and bandwidth shortages. However, millions of laptops, PDAs and other mobile devices remain unused most of the time and this huge resource repository can be potentially utilized in the grid environment. Here, we propose a game theoretic pricing model, to address load balancing issues in mobile grids. In particular, by drawing upon the Nash bargaining solution (NBS), we show that we can obtain an unified framework for addressing such issues as network efficiency, fairness, utility maximization, and pricing. The advantage of this framework is that we have a precise mathematical characterization of the solutions and their properties. Our current endeavor characterizes a two-player alternating-offer bargaining game between the wireless access point (WAP) server and the mobile devices to determine the pricing strategy. This pricing strategy is then made use of to effectively distribute jobs to the mobile devices. Our job allocation scheme maximizes the revenue of the grid user, and yet is comparable to the overall system response time of other load balancing schemes.