Designing Traffic Monitoring Systems for Self-Driving Networks

Abstract

Traffic monitoring is a critical component of self-driving networks. In particular, any system that seeks to automatically manage a network's operation must first be equipped with insights about traffic currently flowing through the network. Typically, dedicated traffic monitoring systems deliver such insights in the form of traffic features to high-level human or automated decision makers. Inspired by the exciting capabilities of programmable dataplanes and the persistent challenges of network management, the research community has focused on improving the flexibility and efficiency of traffic monitoring systems for a variety of management tasks. However, a significant gap remains between the traffic monitoring requirements of practical, deployable self-driving networks and the capabilities of current state-of-the-art systems. This short paper provides a brief background of traffic monitoring systems, discusses how their claims and limitations relate to requirements of self-driving networks, and proposes several open challenges as exciting starting points for future research. Addressing these challenges requires large-scale efforts in traffic monitoring techniques and selfdriving network design, as well as enhanced dialog between researchers in both domains.