EasyQuantile: Efficient Quantile Tracking in the Data Plane

Abstract

Quantile tracking is an essential component of network measurement, where the tracked quantiles of the key performance metrics allow operators to better understand network performance. Given the high network speed and huge volume of traffic, the line-rate packet-processing performance and network visibility of programmable switches make it a trend to track quantiles in the programmable data plane. However, due to the rigorous resource constraints of programmable switches, quantile tracking is required to be both memory and computation efficient to be deployed in the data plane. In this paper, we present EasyQuantile, an efficient quantile tracking approach that has small constant memory usage and involves only hardware-friendly computations. EasyQuantile adopts an adjustable incremental update approach and calculates a pre-specified quantile with high accuracy entirely in the data plane. We implement EasyQuantile on Intel Tofino switches with small resource usage. Trace-driven experiments show that EasyQuantile achieves higher accuracy and lower complexities compared with state-of-the-art approaches.