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A probability-guaranteed adaptive timeout algorithm for high-speed network flow detection

机译:高速网络流量检测的概率保证自适应超时算法

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Collecting network traffic is becoming a more challenging task in passive network measurement due to the rapid growth of link speed. Flow-based network traffic capture and storage provides an efficient way for high-speed network measurement. The paper concentrates on the flow detection issue which is also the premise for further flow-based traffic-analysis and modeling in such challenging environment. Based on the statistical investigation of the correlations between flow size and the maximum packet interarrival time within a flow, we obtain the empirical conditional distribution functions for some popular TCP protocol-based application flows, and then propose a Probability-Guaranteed Adaptive Timeout algorithm (PGAT) for flow termination decision. The assessment criteria for flow termination decision algorithm is systematically developed. Comparisons on flow generation ratio, flow intact ratio, and mean flow extra retaining time metrics indicate that the PGAT algorithm can obtain more attractive performance than other related works.
机译:由于链路速度的快速增长,收集网络流量已成为被动网络测量中更具挑战性的任务。基于流的网络流量捕获和存储为高速网络测量提供了一种有效的方法。本文着重于流量检测问题,这也是在这种充满挑战的环境中进一步进行基于流量的流量分析和建模的前提。基于对流大小与流中最大数据包到达时间之间的相关性的统计调查,我们获得了一些流行的基于TCP协议的应用流的经验条件分布函数,然后提出了一种概率保证的自适应超时算法(PGAT) )以决定流量终止。系统制定了流量终止决策算法的评估标准。流量生成率,流量完整率和平均流量额外保留时间度量标准的比较表明,PGAT算法可以获得比其他相关工作更具吸引力的性能。

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