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Distributed Resource Allocation for Data Center Networks: A Hierarchical Game Approach

机译:数据中心网络的分布式资源分配:分层游戏方法

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The increasing demand of data computing and storage for cloud-based services motivates the development and deployment of large-scale data centers. This paper studies the resource allocation problem for the data center networking system when multiple data center operators (DCOs) simultaneously serve multiple service subscribers (SSs). We formulate a hierarchical game to analyze this system where the DCOs and the SSs are regarded as the leaders and followers, respectively. In the proposed game, each SS selects its serving DCO with preferred price and purchases the optimal amount of resources for the SS's computing requirements. Based on the responses of the SSs’ and the other DCOs’, the DCOs decide their resource prices so as to receive the highest profit. When the coordination among DCOs is weak, we consider all DCOs are noncooperative with each other, and propose a sub-gradient algorithm for the DCOs to approach a sub-optimal solution of the game. When all DCOs are sufficiently coordinated, we formulate a coalition game among all DCOs and apply Kalai-Smorodinsky bargaining as a resource division approach to achieve high utilities. Both solutions constitute the Stackelberg Equilibrium. The simulation results verify the performance improvement provided by our proposed approaches.
机译:基于云的服务的数据计算和存储需求的越来越大促激励大规模数据中心的开发和部署。本文研究了多个数据中心运营商(DCOS)同时为多个服务订阅者(SSS)提供的数据中心网络系统的资源分配问题。我们制定分层游戏,分析该系统,其中分别将DCOS和SSS视为领导者和追随者。在拟议的游戏中,每个SS选择其服务DCO,优先价格并购买SS计算要求的最佳资源量。根据SSS'和其他DCOS的回答,DCOS决定其资源价格以获得最高利润。当DCOS之间的协调较弱时,我们认为所有DCO都是彼此非自由作的,并提出了一种用于DCOS的子梯度算法,以接近游戏的次优算法。当所有DCO都足够协调时,我们在所有DCO中制定了联盟游戏,并将Kalai-Smorodinsky讨价还价作为资源划分方法,以实现高公用事业。这两种解决方案都构成了Stackelberg均衡。仿真结果验证了我们提出的方法提供的性能改进。

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