INVEST: Flow-Based Traffic Volume Estimation in Data-Plane Programmable Networks

The emergence of programmable data planes in Software-Defined Networks enables the execution of various monitoring tasks directly in network devices, overcoming the need to deliver huge amounts of information to a controller that must then process it at scale. In this paper, we aim to solve a fundamental problem arising when exploiting programmable data planes for network-wide monitoring: how to estimate the overall number of packets in the network (i.e., the traffic volume), and the related number and size of flows, while avoiding packet double counting. Most existing works solve this problem by ensuring that each packet is counted only once on its path, which limits routing or requires coordination among devices. We propose a different approach, INVEST, a flow-based traffic volume estimator for P4-based switches, that relies on and can reuse commonly employed data structures while naturally solving the double-counting problem. We theoretically analyze and experimentally evaluate our solution, which we implemented in a real P4 carrier-grade switch, finding that it is accurate, memory-efficient, and can process packets at line rate.