AccuPIPE: Accurate Heavy Flow Detection in the Data Plane Using Programmable Switches

Identifying heavy flows, i.e., flows with large packet counts during a pre-defined time window, is vital for many network applications. The task of real-time heavy flow detection in data plane is challenging due to high switching speed (100 Gbps), a large number of concurrent flows (millions of concurrent flows), and small memory footprint requirement. In this paper, we dissect the key factors that affect the existing detection scheme’s accuracy, and propose AccuPipe, a new detection scheme with intelligent flow entry replacement strategies. The simulation results show that the new scheme is able to efficiently utilize all flow entries in the detection pipeline, and detects more than 850 heavy flows (out of top 1,000) using a small amount of memory (1,000 flow entries, roughly equivalently to 18KB memory) with reasonable reporting overhead. This represents a 76% improvement over HashPIPE scheme, which detects on average 484 heavy flows (out of top 1,000) in the same setting. In addition, we investigate the performance of different flow entry replacement strategies, and report their pros and cons.