Enabling Intelligent In-Network Computing for Cloud Systems

With the network infrastructure becoming highly programmable, it is time to rethink the role of networks in the cloud computing landscape beyond just packet delivery. The network itself emerges as a computing platform with a unique advantage of full network visibility. This project enables advanced approximate telemetry (e.g., sketches) with relevant applications on programmable networks (e.g., programmable switches, SmartNICs, and FPGAs) for cloud system management. Specifically, we will develop a cloud-native, approximate telemetry framework to offer low-overhead, fine-grained, real-time visibility into the underlying network traffic. Moving forward, this line of research with “intelligent” networking aims to provide insights and system abstractions to improve the performance, reliability, and security of cloud systems.

Funding Source: Red Hat Enabling Intelligent In-Network Computing for Cloud Systems, 1/1/2022 to 12/31/2022

Publications

[VLDB] Enabling Efficient and General Subpopulation Analytics In Multidimensional Data Streams
Antonis Manousis, Zhuo Cheng, Ran Ben Basat, Zaoxing Liu, Vyas Sekar
in VLDB’22

Software

[Hydra] Github