Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

The computing demand for massive applications has led to the ubiquitous deployment of
computing power. This trend results in the urgent need for higher-level computing resource …

With the development of software-defined network and programmable data-plane
technology, in-band network telemetry has emerged. In-band network telemetry technology …

Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Network traffic measurement is central to successful network operations, especially for
today's hyper-scale networks. Although existing works have made great contributions, they …

Using programmable network devices to aid in-network machine learning has been the
focus of significant research. However, most of the research was of a limited scope …

In this work, we ask: what would it take for, say, a campus network operator to tell the
network, using natural language, to" Inspect traffic for the dorm"? How could the network …

The advent of switches with programmable dataplanes has enabled the rapid development
of new network functionality, as well as providing a platform for acceleration of a broad …

Programmable networks support a wide variety of applications, including access control,
routing, monitoring, caching, and synchronization. As demand for applications grows, so …

This paper describes Trio, a programmable chipset used in Juniper Networks' MX-series
routers and switches. Trio's architecture is based on a multi-threaded programmable packet …