一种业务流自适应尽力采样方法

A Best-Effort Adaptive Sampling Method for Flow-Based Traffic Monitoring

基于业务流的网络流量监测是网络管理、运维、实现基于业务的计费、流量工程等的重要手段.精确、高效的采样技术是实现高速网络流量业务流监测分析的重要技术.基于分段采样思想提出一种尽力最优的自适应随机采样方法,实现特大业务流的精确估计,其中把监测系统本身的处理能力作为选择采样概率的参数.实验结果显示算法能够很好地调节采样概率,使得采样包速率基本等于预先设定的监测系统的处理能力.

Flow-based traffic monitoring and analysis is widely used in usage-accounting, QoS monitoring, attack detection and network traffic engineering. Accurate and efficient sampling technology is required by implementation of high-speed network traffic analysis based on flow. The packets dealing ability of the monitoring system is a necessary parameter needed to be considered due to the limitation of hardware and software designation. In this paper, one best-effort adaptive sampling method is proposed according to the characteristics of traffic flow and stratified sampling technology. The goal of the method is to take as more as sampled points within the process ability of the monitoring system. The experiments show that the method can adjust the sampling probability very well.