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Minimizing Transient Congestion during Network Update in Data Centers

机译:在数据中心的网络更新期间最小化瞬态拥塞

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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:为了最大限度地提高数据中心网络利用率,SDN控制平面需要经常将数据平面更新为网络条件的变化。由于每个交换机独立和异步地更新其流动表,所以状态转换 - 如果直接从初始阶段完成 - 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具有多个阶段的无充塞更新计划,每个阶段都有与更新订单无关的属性没有拥塞。然而,无拥塞更新需要部分链路容量空置,并降低昂贵的网络基础架构的利用率。此外,它涉及求解一系列LP,这缓慢并且不刻度。在本文中,考虑到中间阶段的数量,研究了在网络更新期间最小化瞬态拥塞的更一般性问题。这在更新速度和瞬态拥塞之间进行了折衷,并允许操作员导航更广泛的设计空间以进行网络更新。我们制定最小拥塞更新问题(MCUP)作为优化程序,并证明其硬度。我们提出了一种近似算法和贪婪的改进算法,以有效且可扩展的方式找到更新序列。与Mininet的广泛实验表明,与本领域相比,我们的解决方案将更新时间减少50%,并将控制开销节省30%。

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