Enabling Heavy Flow Detection on Resource-Constrained Data Plane

In an era of rapidly increasing network speeds and expanding infrastructures, the demand for real-time and accurate network measurement tasks by network management has progressively heightened. Among these tasks, heavy flow detection has received sustained attention due to its broad application in areas such as traffic scheduling and congestion control. Concurrently, as a growing number of network services are deployed to the data plane, the already scarce resources of the data plane face even stricter constraints in multi-task scenarios. Hence, this paper proposes a heavy flow detection method aimed at resource-constrained scenarios, implementing a lightweight and hardware-software integrated real-time heavy flow detection on a data plane based on FPGA programmable switches. By designing an accurate flow table utilizing FPGA resource characteristics and optimizing the implementation of the sketch algorithm in hardware, our method significantly reduces the resource overhead of the data plane while conducting real-time detection of large network flows. Tests conducted with different real network traffic and a 4×10Gbps programmable network card have demonstrated that, with minimal hardware resources and minimal interference with network forwarding services, the real-time heavy flow detection precision of our method can reach more than 97%.