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A Scalable Approach to Avoid Incast Problem from Application Layer

机译:一种可扩展的方法,可以避免应用层的内播问题

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摘要

With the development of distributed computing technology and cloud computing technology, the amount of data is rising dramatically, as well as the number of datacenters, where we keep these data for long periods. In these datacenters, TCP protocol is still widely used in most of the network traffic. On the other hand, TCP protocol can also result in severe goodput collapse in a high bandwidth and low latency datacenter environment. One of the problems is called incast problem. In order to efficiently utilize the bandwidth of distributed systems such as datacenter environments, some traffic control mechanisms should be very necessary. In this paper, we discussed about an application layer control mechanism to improve the performance of certain traffic pattern which may cause incast problem. The main idea is to make the data flows be staggered and transferred in serialized manner. We conducted both simulation-based and real-machine-based experiments. In the real-machine-based experiments, we conducted both small scale test and large scale test. We find out that the proposed approach, staggered flows, is able to avoid incast problem and to make the performance better in most cases. Also, this paper shows the potential of scalability that this approach can keep the performance well with the increment of node quantity.
机译:随着分布式计算技术和云计算技术的发展,数据量以及用于长期保存这些数据的数据中心的数量正在急剧增加。在这些数据中心中,TCP协议仍被大多数网络流量广泛使用。另一方面,TCP协议还会在高带宽和低延迟的数据中心环境中导致严重的吞吐量崩溃。问题之一被称为铸件问题。为了有效利用分布式系统(例如数据中心环境)的带宽,某些流量控制机制应该非常必要。在本文中,我们讨论了一种应用程序层控制机制,该机制可改善某些流量模式的性能,这可能会导致播客问题。主要思想是使数据流交错并以串行方式传输。我们进行了基于仿真和基于真实机器的实验。在基于真实机器的实验中,我们进行了小规模测试和大规模测试。我们发现,所提出的方法(错开的流程)能够避免浇铸问题,并且在大多数情况下可以提高性能。此外,本文还显示了这种可伸缩性的潜力,即该方法可以随着节点数量的增加而保持性能良好。

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