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A Game Theoretic Resource Allocation Model Based on Extended Second Price Sealed Auction in Grid Computing

机译:基于延长第二次价格密封拍卖网格计算的游戏理论资源分配模型

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—In resource-limited environment, grid users compete for limited resources, and how to guarantee tasks’ victorious probabilities is one of the most primary issues that a resource scheduling model cares. In order to guarantee higher task’s victorious probabilities in grid resources scheduling situations, a novel model, namely ESPSA (Extended Second Price Sealed Auction), is proposed. The ESPSA model introduces an analyst entity, and designs analyst’s prediction algorithm based on Hidden Markov Model (HMM). In ESPSA model, grid resources are sold through second price sealed auction. Moreover, to achieve high victorious probabilities, the user brokers who are qualified to participate in the auctions will predict other players’ bids and then carry out the most beneficial bids. The ESPSA model is simulated based on GridSim toolkit. Simulation results show that the ESPSA model assures a higher victorious probability and superior to other traditional algorithms. Moreover, we analyze the existence of Nash equilibrium based on simulation results, thus, any participant who changes its strategy unilaterally could not make the results better.
机译:-IN资源限制的环境,网格用户竞争有限的资源,以及如何保证任务的胜利概率是资源调度模型所关心的最主要问题之一。为了保证高级任务在网格资源调度情况下的胜利概率,提出了一种小说模型,即ESPSA(延长的第二价密封拍卖)。 ESPSA模型介绍了分析实体,并根据隐马尔可夫模型(HMM)设计了分析师的预测算法。在ESPSA模型中,网格资源通过第二个价格密封拍卖出售。此外,为了实现高胜利概率,有资格参与拍卖的用户经纪人将预测其他玩家的出价,然后进行最有益的出价。基于Gridsim Toolkit模拟ESPSA模型。仿真结果表明,ESPSA模型可确保更高的胜利概率和优于其他传统算法。此外,我们根据仿真结果分析了纳什均衡的存在,因此,任何改变其战略单方面的参与者无法更好地改变结果。

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