组件订阅网络拓扑对大规模数据中心性能扩展的影响
Effects of component-subscription network topology on large-scale data centre performance scaling
摘要：
现代大规模数据中心，例如用于云计算服务提供的数据中心，正变得越来越大，因为这些数据中心的运营商寻求最大化来自规模经济的益处。随着这些尺寸的增加，系统复杂性也随之增加，这通常是有问题的。对数据中心基础设施的自动化“自启动”配置、管理和故障恢复的需求日益增加，但随着要管理的节点数量的增加，许多传统技术的扩展比线性扩展差得多。由于在未来几十年中，中型数据中心的节点数量将增加两到三个数量级，因此在构建此类数据中心之前，尝试探索和理解数据中心中间件的伸缩特性似乎是合理的。在[1]中，我们介绍了SPECI，这是一个模拟器，可以预测大规模数据中心中间件性能的各个方面，重点关注状态变化的影响，例如策略更新或例行节点故障。[...].在[1]中，我们使用了一个第一近似假设，即这种订阅在整个数据中心中完全随机分布。在本文中，我们探讨了引入更现实的约束的内部网络的订阅结构的影响。我们对比了原始结果[…]探索使数据中心的订阅网络具有规则的格子状结构的效果，以及由创建“小世界”和“无标度”网络的参数化网络生成函数产生的半随机网络结构。我们发现，对于分布式中间件拓扑结构，在数据中心进行的任务的结构和分布可以显着影响的中间件所施加的性能开销。
英文摘要：
Modern large-scale date centres, such as those used for cloud computing service provision, are becoming ever-larger as the operators of those data centres seek to maximise the benefits from economies of scale. With these increases in size comes a growth in system complexity, which is usually problematic. There is an increased desire for automated "self-star" configuration, management, and failure-recovery of the data-centre infrastructure, but many traditional techniques scale much worse than linearly as the number of nodes to be managed increases. As the number of nodes in a median-sized data-centre looks set to increase by two or three orders of magnitude in coming decades, it seems reasonable to attempt to explore and understand the scaling properties of the data-centre middleware before such data-centres are constructed. In [1] we presented SPECI, a simulator that predicts aspects of large-scale data-centre middleware performance, concentrating on the influence of status changes such as policy updates or routine node failures. [...]. In [1] we used a first-approximation assumption that such subscriptions are distributed wholly at random across the data centre. In this present paper, we explore the effects of introducing more realistic constraints to the structure of the internal network of subscriptions. We contrast the original results [...] exploring the effects of making the data-centre's subscription network have a regular lattice-like structure, and also semi-random network structures resulting from parameterised network generation functions that create "small-world" and "scale-free" networks. We show that for distributed middleware topologies, the structure and distribution of tasks carried out in the data centre can significantly influence the performance overhead imposed by the middleware.
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