To main content

Cascade: An Edge Computing Platform for Real-time Machine Intelligence

Academic chapter/article/Conference paper
Year of publication
External websites
Involved from NIVA
Andrea Merlina
Weijia Song, Yuting Yang, Thompson Liu, Andrea Merlina, Thiago Garrett, Roman Vitenberg, Lorenzo Rosa, Aahil Awatramani, Zheng Wang, Ken Birman


Intelligent IoT is a prerequisite for societal priorities such as a smart power grid, smart urban infrastructures and smart highways. These applications bring requirements such as real-time guarantees, data and action consistency, fault-tolerance, high availability, temporal data indexing, scalability, and even self-organization and self-stabilization. Existing platforms are oriented towards asynchronous, out of band upload of data to the cloud: Important functionality, but not enough to address the need. Cornell's Cascade project seeks to close the gap by creating a new platform for hosting ML and AI, optimized to achieve sharply lower delay and substantially higher bandwidth than in any existing platform. At the same time, Cascade introduces much stronger guarantees - a mix that we believe will be particularly appealing in applications where events should trigger a quick and trustworthy response. This short paper is intended as a brief overview of the effort, with details to be published elsewhere.