Unbiased Real-time Traffic Sketching

In network measurement, sliding window measurement has the advantage of providing recent and timely measurement results. Recently, sketches have become the most popular method of conducting flow-level network measurements due to their favorable trade-off between small memory overhead and high measurement accuracy. However, it remains a challenge that no current sketches are able to support unbiased estimation toward flow size measurement, which can improve the performance of tasks including network diagnoses, delay measurement and heavy hitter detection. In this paper, we propose the first work that achieves unbiased flow size measurement in sliding windows, namely Unbiased Cleaning sketch (UC sketch) . The key technique of the UC sketch is Unbiased Cleaning which can remove outdated keys from the sliding windows in a balanced way. Besides, we significantly reduce the variance of flow size by two optimization techniques, namely Linear Scaling and Column Randomizing . To prove the result, we conduct rigorous mathematical analysis and reasonable experiments. All related source codes are open-sourced at Github anonymously.