ResQueue:一个更智能的数据中心流调度程序

Hamed Rezaei, Balajee Vamanan
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引用次数: 2

摘要

数据中心托管多种应用程序:前台应用程序执行分布式查找,以便为用户查询提供服务;后台应用程序执行批处理任务,如数据重组、备份和复制。虽然后台流产生的负载最多,但前台应用程序产生的流数量最多。由于来自这两种类型的应用程序的数据包在交换机上竞争网络带宽,因此应用程序的性能对调度机制很敏感。现有调度器使用流大小来区分关键流和非关键流。然而,最近对数据中心工作负载的研究表明,大多数流都很小(例如,大多数流仅由少量数据包组成)。根据最近的研究结果,我们做出了关键的观察,因为大多数流量很小,流量大小不足以区分关键流量和非关键流量,因此现有的流量调度器不能实现预期的优先级。在本文中,我们介绍了ResQueue,它结合流大小和数据包历史来计算每个流的优先级。我们的评估表明,与最先进的流调度机制相比,ResQueue将短流的尾流完成时间提高了60%。
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ResQueue: A Smarter Datacenter Flow Scheduler
Datacenters host a mix of applications: foreground applications perform distributed lookups in order to service user queries and background applications perform batch processing tasks such as data reorganization, backup, and replication. While background flows produce the most load, foreground applications produce the most number of flows. Because packets from both types of applications compete at switches for network bandwidth, the performance of applications is sensitive to scheduling mechanisms. Existing schedulers use flow size to distinguish critical flows from non-critical flows. However, recent studies on datacenter workloads reveal that most flows are small (e.g., most flows consist of only a handful number of packets). In light of recent findings, we make the key observation that because most flows are small, flow size is not sufficient to distinguish critical flows from non-critical flows and therefore existing flow schedulers do not achieve the desired prioritization. In this paper, we introduce ResQueue, which uses a combination of flow size and packet history to calculate the priority of each flow. Our evaluation shows that ResQueue improves tail flow completion times of short flows by up to 60% over the state-of-the-art flow scheduling mechanisms.
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