A2C: Anti-Attack Counters for Traffic Measurement

Flow-level sampling methods have been widely studied and extensively employed in network traffic measurement systems. Current approaches mainly focus on improving the performance under normal traffic. However, traffic anomalies are now becoming more prevalent and severe in the internet, which poses great challenges to the traffic measurement. Existing solutions targeted such scenario have either low accuracy or high memory usage. The proposed sampling mechanism can adapt to the network condition automatically and collect more information even under severe traffic attacks. Theoretical analysis on accuracy and resource requirement is presented in the paper.