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

The end of Moore's Law and Dennard Scaling has slowed processor improvements in the
past decade. While multi-core processors have improved performance, they are limited by …

SmartNICs are on the rise as a packet processing platform, with the trend towards a uniform
P4 programming model. However, unleashing SmartNIC packet processing performance in …

Data-plane programmability is now mainstream. As we find more use cases, deployments
need to be able to run multiple packet-processing modules in a single device. These are …

Packet schedulers play a crucial role in determining the order in which packets are served.
They achieve this by assigning a rank to each packet and sorting them based on these …

Our community has made significant progress in developing programmable network
infrastructure, starting from the control plane and expanding to the data plane. As a latest …

For security, isolation, metering and other purposes, public clouds today implement complex
network functions at every server. Today's implementations, in software or on FPGAs and …

Online traffic classification enables critical applications such as network intrusion detection
and prevention, providing Quality-of-Service, and real-time IoT analytics. However, with …

We make a case for in-network Continual Learning as a solution for seamless adaptation to
evolving network conditions without forgetting past experiences. We propose implementing …

We propose a practical approach to implementing multitenancy on programmable network
switches to make in-network acceleration accessible to cloud users. We introduce a Switch …