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Minimizing Transient Congestion during Network Update in Data Centers

机译:最小化数据中心网络更新过程中的瞬时拥塞

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To maximize data center network utilization, the SDN control plane needs to frequently update the data plane as the network conditions change. Since each switch updates its flow table independently and asynchronously, the state transition -- if done directly from the initial to the final stage -- may result in serious flash congestion and packet loss. Prior work strives to find a congestion-free update plan with multiple stages, each with the property that there will be no congestion independent of the update order. Yet congestion-free update requires part of the link capacity to be left vacant and decreases utilization of the expensive network infrastructure. Further, it involves solving a series of LP, which is slow and does not scale well. In this paper, we study the more general problem of minimizing transient congestion during network update, given the number of intermediate stages. This exposes the tradeoff between update speed and transient congestion, and allows an operator to navigate a broader design space for performing network update. We formulate the minimum congestion update problem (MCUP) as an optimization program and prove its hardness. We propose an approximation algorithm and a greedy improvement algorithm to find the update sequence in an efficient and scalable manner. Extensive experiments with Mininet show that our solution reduces update time by 50% and saves control overhead by 30% compared to state of the art.
机译:为了最大程度地利用数据中心网络,SDN控制平面需要随着网络条件的变化而频繁地更新数据平面。由于每个交换机都独立且异步地更新其流表,因此状态转换(如果直接从初始阶段执行到最终阶段)可能会导致严重的闪存拥塞和数据包丢失。先前的工作致力于找到一个具有多个阶段的无拥塞更新计划,每个阶段都具有不依赖于更新顺序而不会发生拥塞的特性。然而,无拥塞更新要求部分链路容量保持空闲状态,并降低昂贵的网络基础架构的利用率。此外,它涉及解决一系列LP,这很慢且扩展性不佳。在本文中,鉴于中间阶段的数量,我们研究了在网络更新过程中将瞬态拥塞减至最小的更普遍的问题。这暴露了更新速度和瞬时拥塞之间的权衡,并允许操作员在更宽的设计空间中导航以执行网络更新。我们将最小拥塞更新问题(MCUP)制定为优化程序,并证明其难度。我们提出一种近似算法和贪婪改进算法,以高效且可扩展的方式找到更新序列。通过Mininet进行的广泛实验表明,与最新技术相比,我们的解决方案将更新时间减少了50%,并将控制开销节省了30%。

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