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A game-theoretic method of fair resource allocation for cloud computing services

机译:云计算服务公平资源分配的博弈论方法

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As cloud-based services become more numerous and dynamic, resource provisioning becomes more and more challenging. A QoS constrained resource allocation problem is considered in this paper, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation. Game theory is used to solve the problem of resource allocation. A practical approximated solution with the following two steps is proposed. First, each participant solves its optimal problem independently, without consideration of the multiplexing of resource assignments. A Binary Integer Programming method is proposed to solve the independent optimization. Second, an evolutionary mechanism is designed, which changes multiplexed strategies of the initial optimal solutions of different participants with minimizing their efficiency losses. The algorithms in the evolutionary mechanism take both optimization and fairness into account. It is demonstrated that Nash equilibrium always exists if the resource allocation game has feasible solutions.
机译:随着基于云的服务变得越来越多且越来越动态,资源配置变得越来越具有挑战性。本文考虑了QoS约束的资源分配问题,其中服务需求者打算通过请求基于云的网络上的资源使用来解决复杂的并行计算问题,并且每种计算服务的成本取决于计算量。博弈论用于解决资源分配问题。提出了具有以下两个步骤的实用近似解决方案。首先,每个参与者独立解决其最佳问题,而无需考虑资源分配的复用。提出了一种二进制整数规划方法来解决独立优化问题。其次,设计了一种进化机制,该机制改变了不同参与者初始最优解的复用策略,同时将其效率损失降至最低。进化机制中的算法同时考虑了优化和公平性。证明了如果资源分配博弈有可行的解决方案,那么纳什均衡总是存在的。

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