An online framework for flow round trip time measurement

Xinjie Guan, Xili Wan, R. Kawahara, H. Saito
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Abstract

With the advent of high speed links, online flow measurement for, e.g., flow round trip time (RTT), becomes difficult due to the enormous amount of requirements on computational resources. We address this problem by proposing the double-deletion bloom filter (DDBF) scheme, which alleviates potential hash collisions of a standard bloom filter by explicitly deleting used records and implicitly deleting out-of-date records. As a result, it accurately estimates the current TCP flow RTT distribution with limited memory space, even with the appearance of multipath routing and Syn flooding attacks. Theoretical analysis indicates that the DDBF scheme exhibits desirable accuracy with a constant and small amount of memory. We further validate our scheme using real traces and demonstrate significant memory-saving without degrading accuracy.
流量往返时间在线测量框架
随着高速链路的出现,流量往返时间(RTT)等在线流量测量由于对计算资源的巨大需求而变得困难。我们通过提出双删除布隆过滤器(DDBF)方案来解决这个问题,该方案通过显式删除使用过的记录和隐式删除过期记录来减轻标准布隆过滤器的潜在哈希冲突。因此,即使出现了多路径路由和Syn泛洪攻击,它也能在有限的内存空间下准确地估计当前TCP流RTT分布。理论分析表明,DDBF方案具有较高的精度和较小的内存容量。我们使用真实的跟踪进一步验证了我们的方案,并证明了在不降低准确性的情况下显着节省内存。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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