任意分布的服务器选择

Xinjie Li, M. Brockmeyer
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引用次数: 0

摘要

许多应用程序需要选择具有某些理想发行版的服务器。例如,在概率仲裁系统中,随机选取具有固定概率分布的kradicn节点是产生高交集概率仲裁的一种方法。负载平衡应用程序可能需要从具有某些期望分布的服务器中获取多个示例。现有的方法通过控制覆盖图的拓扑结构并对其进行随机游动来实现固定的平稳分布。特别是,现有的方法侧重于实现均匀分布。本文提出使用分布式Hastings-Metropolis算法来实现任何期望的平稳分布,而不需要控制或全局了解覆盖图。新方法促进了良好的负载平衡,因为在决定选择服务器的适当分布时可以考虑异构服务器容量或其他因素
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Server selection with arbitrary distribution
Many applications need to pick servers with some desired distribution. For example, in probabilistic quorum systems, one method to generate quorums with high probability of intersection is to randomly pick kradicn nodes with a fixed probability distribution. Load balancing applications may need to take several samples of the servers with some desired distribution. Existing approaches realize a fixed stationary distribution by controlling the topology of the overlay graph and conducting random walks on it. In particular, existing approaches focus on achieving a uniform distribution. This paper proposes using the distributed Hastings-Metropolis algorithm to achieve any desired stationary distribution without control or global knowledge of the overlay graph. The new method facilitates good load balancing, since heterogeneous server capacity or other factors can be considered in deciding the appropriate distribution by which to pick servers
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