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首页> 外文期刊>Journal of supercomputing >A game theoretical model for profit maximization resource allocation in cloud environment with budget and deadline constraints
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A game theoretical model for profit maximization resource allocation in cloud environment with budget and deadline constraints

机译:具有预算和期限约束的云环境中利润最大化资源分配的博弈模型

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摘要

One significant challenge for the resource allocation in cloud environments is the pricing issue and selection of applicants of cloud resources on the basis of cloud economic parameters. Taking into account the fact that the resource allocation in cloud environments is an economic supply-and demand-based problem, economics-based methods result in better solutions in a shorter period of time. In this paper, using Bayesian method, where each user estimates other rivals' actions in the next step of the auction, a game model for winner determination is proposed. a non-cooperative game theory mechanism based on combinatorial auction in an environment with incomplete information has been proposed to reach Nash equilibrium point and select the winners. Using the proposed method, an improvement of 17% profit was obtained for the cloud provider and a 12 % boost was seen in the sold resources. The objective function suggested for bidding converged to the solution in all cases and was stable. In the following, it was proved that the proposed model has the possibility of attaining the best local bid.
机译:云环境中资源分配的一项重大挑战是定价问题以及根据云经济参数选择云资源的申请人。考虑到云环境中的资源分配是一个基于经济供需的问题,基于经济学的方法可在较短的时间内提供更好的解决方案。在本文中,使用贝叶斯方法,其中每个用户在拍卖的下一步中估计其他竞争对手的行为,提出了一种用于确定获胜者的游戏模型。提出了一种在信息不完全的环境下基于组合拍卖的非合作博弈机制,以达到纳什均衡点并选择获胜者。使用建议的方法,云提供商的利润提高了17%,售出的资源增长了12%。建议的目标函数在所有情况下都收敛到解决方案并且稳定。在下文中,证明了所提出的模型具有获得最佳本地出价的可能性。

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