A game theory based pricing strategy for job allocation in mobile grids
A game theory based pricing strategy for job allocation in mobile grids
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DOI：
10.1109/ipdps.2004.1303020
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发表时间：
2004-04
期刊：
影响因子：
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通讯作者：
P. Ghosh;Nirmalya Roy;Sajal K. Das;K. Basu
中科院分区：
文献类型：
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作者：
P. Ghosh;Nirmalya Roy;Sajal K. Das;K. Basu
仅提供摘要形式。本文通过提出一种公平的定价策略和一种最优的静态作业分配方案，实现了移动的网格计算的愿景。移动的设备还没有被集成到网格计算平台中，主要是由于它们在处理和存储容量、功率和带宽短缺方面的固有限制。然而，数以百万计的膝上型计算机、PDA和其他移动的设备在大多数时间内都没有被使用，这个巨大的资源库可以在网格环境中得到潜在的利用。在这里，我们提出了一个博弈论的定价模型，以解决负载平衡问题，在移动的网格。特别是，通过借鉴纳什讨价还价的解决方案（NBS），我们表明，我们可以获得一个统一的框架来解决网络效率，公平性，效用最大化和定价等问题。这个框架的优点是，我们有一个精确的数学表征的解决方案和他们的属性。我们目前的奋进的特点是一个两个球员之间的无线接入点（WAP）服务器和移动的设备，以确定定价策略的交替提供讨价还价的游戏。然后利用该定价策略将作业有效地分配给移动的设备。我们的作业分配方案最大限度地提高了网格用户的收入，但与其他负载平衡方案的整体系统响应时间相当。
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.