最大-最小公平分配的渐近最优性

H. Ye, D. Yao
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引用次数: 0

摘要

在由一组服务器组成的随机网络中处理多类作业。每个作业类都需要并发占用要处理的服务器子集,并且在一流的处理器共享机制中,每个服务器在作业类之间共享。在网络的每个状态下,服务器容量根据所谓的max-min公平策略在作业类之间分配。我们推导了在这种资源控制策略下网络的流动和扩散极限。此外,我们提供了与流体极限相关的不动点状态的表征,并确定了在扩散状态下最小化的代价函数
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asymptotic Optimality of the Max-Min Fair Allocation
Multiple classes of jobs are processed in a stochastic network that consists of a set of servers. Each class of jobs requires a concurrent occupancy of a subset of servers to be processed, and each server is shared among the job classes in a head-of-the-line processor-sharing mechanism. In each state of the network, the server capacities are allocated among the job classes according to the so-called max-min fair policy. We derive the fluid and diffusion limits of the network under this resource control policy. Furthermore, we provide a characterization of the fixed-point state associated with the fluid limit, and identify a cost function that is minimized in the diffusion regime
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