Providing In-network Support to Coflow Scheduling
Providing In-network Support to Coflow Scheduling
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DOI：
10.1109/netsoft51509.2021.9492530
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
C. H. Benet;A. Kassler;G. Antichi;Theophilus A. Benson;Gergely Pongrácz
中科院分区：
文献类型：
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作者：
C. H. Benet;A. Kassler;G. Antichi;Theophilus A. Benson;Gergely Pongrácz
新兴的分布式应用程序（如大数据分析）会生成大量的流，这些流会在数据中心网络中同时传输数据。为了提高它们的性能，需要考虑这种流集合的行为，即，共同流动，而不是单独流动。国家的最先进的解决方案实现近最优的完成时间，通过不断重新排序未完成的coflows在终端主机和使用网络prioritys.This表明，动态变化的流优先级在终端主机，不考虑在飞行中的数据包，可能会导致高度的数据包重新排序，从而施加压力的拥塞控制和潜在的危害网络性能的存在下，浅缓冲区的交换机。我们提出了一种新的解决方案，集成了基于端主机的coflow排序与基于数据包历史的网络调度。我们的评估表明，pallow提高了coflow完成时间后，国家的最先进的解决方案，高达34%的变化负载。
Emerging distributed applications, such as big data analytics, generate a large number of flows that concurrently transport data across data center networks. To improve their performance, it is required to account for the behavior of such a collection of flows, i.e., coflows, rather than individual ones. State-of-the-art solutions achieve near-optimal completion time by continuously reordering unfinished coflows at the end-host and using network priorities.This paper shows that dynamically changing flow priorities at the end-host, without considering in-flight packets, can cause high degrees of packet reordering, thus imposing pressure on the congestion control and potentially harming network performance in the presence of switches with shallow buffers. We present pCoflow, a new solution that integrates end-host based coflow ordering with in-network scheduling based on packet history. Our evaluation shows that pCoflow improves in coflow completion time upon state-of-the-art solutions by up to 34% for varying loads.