DISCO: Memory Efficient and Accurate Flow Statistics for Network Measurement
DISCO: Memory Efficient and Accurate Flow Statistics for Network Measurement
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DOI：
10.1109/icdcs.2010.57
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发表时间：
2010-06
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通讯作者：
Chengchen Hu;B. Liu;Hongbo Zhao;Kai Chen;Yan Chen;Chunming Wu;Y. Cheng
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作者：
Chengchen Hu;B. Liu;Hongbo Zhao;Kai Chen;Yan Chen;Chunming Wu;Y. Cheng
网络被动测量的一个基本任务是收集流量统计信息，用于网络状态表征。随着互联网链路速度和流量的不断增加，对测量设备的内存大小和内存带宽的要求越来越高，流量统计成为一个巨大的挑战。在本文中，我们提出了一个折扣计数（DISCO）的方法，这是专为流量的大小和流量计数。对于长度为l的每个输入分组，DISCO以小于l的增量增加分配给该流的对应计数器。通过对计数器更新规则和逆估计的精心设计，DISCO在提供准确的无偏估计器的同时节省了内存消耗。理论分析和仿真与合成和真实的痕迹的方法进行了彻底的评估。结果表明，在相同的计数器尺寸下，DISCO比相关工作更准确。DISCO还在网络处理器Intel IXP 2850上实现，并进行了性能测试。IXP 2850仅使用一个微引擎（ME），在传统的流量模式下，吞吐量可以达到11.1Gbps，并且吞吐量几乎与所使用的ME的数量呈线性增长。
A basic task in network passive measurement is collecting flow statistics information for network state characterization. With the continuous increase of Internet link speed and the number of flows, flow statistics has become a great challenge due to the demanding requirements on both memory size and memory bandwidth in measurement devices. In this paper, we propose a DIScount COunting (DISCO) method, which is designed for both flow size and flow volume counting. For each incoming packet of length l, DISCO increases the corresponding counter assigned to the flow with an increment that is less than l. With an elaborate design on the counter update rule and the inverse estimation, DISCO saves memory consumption while providing an accurate unbiased estimator. The method is evaluated thoroughly under theoretical analysis and simulations with synthetic and real traces. The results demonstrate that DISCO is more accurate than related work given the same counter size. DISCO is also implemented on network processor Intel IXP2850 for performance test. Using only one MicroEngine (ME) in IXP2850, the throughput can reach up to 11.1Gbps under a traditional traffic pattern, and it increases almost linearly with the number of MEs employed.