PA-Sketch: A Fast and Accurate Sketch for Differentiated Flow Estimation
Sitan Li, Jiawei Huang, Wenlu Zhang, Jing Shao · 2023
Due to the ability to maintain good accuracy and high throughput with limited memory resources, sketch has gained wide deployment and application for approximate flow estimation. However, most existing sketch approaches ignore the distinctions between flow priorities, though the high-priority flows are relatively scarce but hold significant information. Therefore, a class of priority-aware sketches has appeared recently to provide differentiated measurement accuracy for flows with different priorities. Unfortunately, it is challenging for these priority-aware sketches to strike a good balance between accuracy and throughput. To address this issue, we propose a priority-adaptive architecture PA-Sketch, which utilizes priority-aware hash to dynamically allocate appropriate numbers of hash functions for different flows according to their priorities. For the scenarios we experimented, we observed that PA-Sketch significantly improves accuracy while minimizing the hash overhead. Compared to the state-of-the-art priority-aware sketches, PA-Sketch achieves around 4.83x higher accuracy and 1.83x higher F1 score for high-priority flows on average, meanwhile maintaining slight accuracy loss for low-priority flows.