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Exploring Token-Oriented In-Network Prioritization in Datacenter Networks

机译:在数据中心网络中探索面向令牌的网络内优先级

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In memory computing and high-end distributed storage demand low latency, high throughput, and zero data loss simultaneously from datacenter networks. Existing reactive congestion control approaches cannot both minimize queuing latency and ensure zero data loss. A token-oriented proactive approach can achieve them together by controlling congestion even before sending data packets. However, state-of-the-art token-oriented approaches only strive to optimize network-level metrics: maximizing throughput while achieving flow-level fairness. This article answers the question of how to support objective-aware traffic scheduling in token-oriented approaches. The novelty of Token-Oriented in-network Prioritization (TOP) is that it prioritizes tokens instead of data packets. We make three contributions. Via simulations over a hypothetical TOP system, our first contribution is demonstrating the potential performance gain that can be brought by TOP. Second, we investigate the applicability of TOP. Although the overhead of enabling necessary TOP features in switches is trivial, we find that mainstream commodity datacenter switches do not support them. We hence propose a readily-deployable remedy to achieve in-network prioritization by pushing both switch and end-host hardware capacity to an extreme end. Lastly, we implement a running TOP system with Linux hosts and commodity switches, and evaluate TOP in testbeds and with large-scale simulations for various scenarios.
机译:在内存计算和高端分布式存储中,数据中心网络需要低延迟,高吞吐量和零数据丢失。现有的反应性拥塞控制方法既不能最小化排队等待时间又不能确保零数据丢失。面向令牌的主动方法甚至可以在发送数据包之前通过控制拥塞来实现它们。但是,最新的面向令牌的方法仅努力优化网络级指标:在实现流级公平性的同时最大化吞吐量。本文回答了如何在面向令牌的方法中支持目标感知流量调度的问题。面向令牌的网络内优先级(TOP)的新颖之处在于,它对令牌而不是数据包进行了优先级排序。我们做出三点贡献。通过在假设的TOP系统上进行的仿真,我们的第一项贡献就是证明TOP可以带来潜在的性能提升。其次,我们研究TOP的适用性。尽管在交换机中启用必要的TOP功能的开销很小,但我们发现主流的商用数据中心交换机不支持它们。因此,我们提出了一种易于部署的补救措施,可以通过将交换机和终端主机的硬件容量都推到极限来实现网络优先级。最后,我们使用Linux主机和商用交换机实现一个正在运行的TOP系统,并在测试平台和针对各种场景的大规模仿真中评估TOP。

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