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Updating Data-Center Network With Ultra-Low Latency Data Plane

机译:使用超低延迟数据平面更新数据中心网络

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摘要

Due to the asynchronous and distributed nature of the data plane, the transition from the initial to final state may result in serious transient congestion in software-defined networking (SDN). Moreover, with the rapid development of ultra-low latency network in data-centers, the control loop between the control and data plane becomes much longer than the ultra-low latency communication in the data plane. In this case, traffic surges significantly in the data plane during the network reconfiguration process, and it becomes harder for the SDN controllers to manipulate the update operations as they expect. In this paper, we consider the traffic variation during the network update and model it as a novel minimum demand violation problem (MDVP). Later, we prove its hardness, and propose a heuristic approximation algorithm to approach the optimal result. Our method brings flexibility for network operators to make a trade-off between the network congestion and update speed. Experiments show that our method can halve the intermediate network states and reduce the demand violation ratio by 36.7 % compared to the state-of-the-art.
机译:由于数据平面的异步和分布式性质,从初始到最终状态的转换可能导致软件定义网络(SDN)中的严重瞬态拥塞。此外,随着数据中心的超低延迟网络的快速发展,控制和数据平面之间的控制环路变得远比数据平面中的超低延迟通信长得多。在这种情况下,在网络重新配置过程中,数据平面中的流量飙升,并且SDN控制器更难以操纵更新操作。在本文中,我们考虑网络更新期间的流量变化,并将其模拟为新的最小需求违规问题(MDVP)。后来,我们证明了其硬度,并提出了一种启发式近似算法来接近最佳结果。我们的方法为网络运营商带来了灵活性,在网络拥塞和更新速度之间进行权衡。实验表明,与现有技术相比,我们的方法可以将中间网络状态降低,并将需求违规比率降低36.7%。

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