基于非完全信息博弈的网格资源分配模型

针对网格计算环境动态,异构和分布的特性以及网格资源分配中资源利用率低、效益不均等问题,结合微观经济学理论,建立了一种多赢家式的网格资源拍卖模型(muti-winners auction model,简称MWAM).将隐马尔可夫模型应用在网格用户t时刻出价状态预测方面,并结合分配算法计算出能够获得所需资源的概率；并且在原有资源分配机制的基础上,结合非完全信息纳什均衡理论设计了一种多赢家拍卖算法.从理论上证明了资源分配结束后系统收益最大,且本模型符合微观经济学中的激励相容性与个人理性准则.实验模拟在验证了隐马尔可夫预测的可行性的同时,又与几种具有代表性的算法相比较,从资源利用率、系统总收益等方面突显了本模型的优势.

Grid Resource Allocation Model Based on Incomplete Information Game

Considering the characteristics of the grid computing environment,dynamic,heterogeneous and distributional,and the problem of the low utilization ratio of resources and benefit imbalance in the grid resource distribution,this paper proposes a grid resource auction model which is multi-winners and based on the microeconomics theory.The contributions of this paper are listed as follows: first the study predicts the status of consumer’s bidding price using the hidden Markov model;second,the paper presents the multi-winners auction model using Nash equilibrium of the incomplete information game,where it could enhance the utilizable rate of resources;thirdly,the condition of dominant strategy incentive compatibility is analyzed;finally,the paper proves the profits both of buyers and the seller all are maximal.Moreover,the utilizable ratio of the resource is proved to be increased through the contradistinctive experiment with other algorithms.