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A Fast and Compact Invertible Sketch for Network-Wide Heavy Flow Detection
IEEE/ACM Transactions on Networking ( IF 3.0 ) Pub Date : 2020-08-06 , DOI: 10.1109/tnet.2020.3011798
Lu Tang , Qun Huang , Patrick P. C. Lee

Fast detection of heavy flows (e.g., heavy hitters and heavy changers) in massive network traffic is challenging due to the stringent requirements of fast packet processing and limited resource availability. Invertible sketches are summary data structures that can recover heavy flows with small memory footprints and bounded errors, yet existing invertible sketches incur high memory access overhead that leads to performance degradation. We present MV-Sketch, a fast and compact invertible sketch that supports heavy flow detection with small and static memory allocation. MV-Sketch tracks candidate heavy flows inside the sketch data structure via the idea of majority voting, such that it incurs small memory access overhead in both update and query operations, while achieving high detection accuracy. We present theoretical analysis on the memory usage, performance, and accuracy of MV-Sketch in both local and network-wide scenarios. We further show how MV-Sketch can be implemented and deployed on P4-based programmable switches subject to hardware deployment constraints. We conduct evaluation in both software and hardware environments. Trace-driven evaluation in software shows that MV-Sketch achieves higher accuracy than existing invertible sketches, with up to $3.38\times $ throughput gain. We also show how to boost the performance of MV-Sketch with SIMD instructions. Furthermore, we evaluate MV-Sketch on a Barefoot Tofino switch and show how MV-Sketch achieves line-rate measurement with limited hardware resource overhead.

中文翻译:

用于网络范围内大流量检测的快速紧凑的可逆草图

由于对快速分组处理的严格要求和有限的资源可用性,快速检测大量网络流量中的大流量(例如,沉重的击打者和沉重的更换者)具有挑战性。可逆草图是摘要数据结构,可以用较小的内存占用空间和有限的错误来恢复繁重的数据流,但是现有的可逆草图会导致较高的内存访问开销,从而导致性能下降。我们提出了MV-Sketch,这是一种快速而紧凑的可逆草图,它支持使用少量和静态内存分配进行大流量检测。MV-Sketch通过多数表决的思想跟踪草图数据结构内部的候选大量流,从而在更新和查询操作中都招致较小的内存访问开销,同时实现了很高的检测精度。我们对内存使用情况进行理论分析,本地场景和全网络场景中MV-Sketch的性能和准确性。我们进一步展示了如何在受硬件部署约束的情况下,在基于P4的可编程交换机上实施和部署MV-Sketch。我们在软件和硬件环境中进行评估。软件中的跟踪驱动评估表明,MV-Sketch比现有的可逆草图具有更高的精度,最高可达 $ 3.38 \次$ 吞吐量提高。我们还将展示如何使用SIMD指令提高MV-Sketch的性能。此外,我们评估了Barefoot Tofino交换机上的MV-Sketch,并显示了MV-Sketch如何在有限的硬件资源开销下实现线速测量。
更新日期:2020-08-06
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