选择性报告减轻重击手探测控制面负担

Zijun Hang, Lin Yang, Jun Zhang, Yongjie Wang
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引用次数: 0

摘要

草图算法易于在低内存开销的情况下实时准确地检测出重磅炸弹。然而,传统的网络测量智慧主要集中在两个关键属性:准确性和内存效率,只针对数据平面。本文旨在通过合理协调数据平面和控制平面的相互作用,实现重拳检测的及时性和通信效率,从而进一步减轻控制平面的负担。结果表明,我们在保持重磅攻击检测精度的同时,将延迟从微秒减少到几乎为零,通信开销最多减少70%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relieve the Control Plane Burdens in Heavy Hitter Detection with Selective Report
Sketch algorithms are apt at detecting Heavy Hitters accurately at real time with low memory overhead. However, traditional wisdom of network measurement mainly concentrates on the two key properties: accuracy and memory-efficiency, which only targets the data plane. This paper aims to achieve timeliness and communication-efficiency in Heavy Hitter detection by properly coordinating the interplay of the data plane and the control plane, thus further relieve the control plane burdens. Results show we maintain the accuracy in Heavy Hitter detection while reduce the delay from microseconds to nearly zero and communication overhead by at most 70%.
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