Back To Schedule
Friday, July 12 • 11:05am - 11:25am
EdgeWise: A Better Stream Processing Engine for the Edge

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Many Internet of Things (IoT) applications would benefit if streams of data could be analyzed rapidly at the Edge, near the data source. However, existing Stream Processing Engines (SPEs) are unsuited for the Edge because their designs assume Cloud-class resources and relatively generous throughput and latency constraints.

This paper presents EdgeWise, a new Edge-friendly SPE, and shows analytically and empirically that EdgeWise improves both throughput and latency. The key idea of EdgeWise is to incorporate a congestion-aware scheduler and a fixed-size worker pool into an SPE. Though this idea has been explored in the past, we are the first to apply it to modern SPEs and we provide a new queue-theoretic analysis to support it. In our single-node and distributed experiments we compare EdgeWise to the state-of-the-art Storm system. We report up to a 3x improvement in throughput while keeping latency low.


Xinwei Fu

Virginia Tech

Talha Ghaffar

Virginia Tech

James C. Davis

Virginia Tech

Dongyoon Lee

Virginia Tech

Friday July 12, 2019 11:05am - 11:25am PDT
USENIX ATC Track II: Grand Ballroom VII–IX