New Paper: OpenRTiST -- End-to-End Benchmarking for Edge Computing

The growth of edge computing depends on large-scale deployments of edge
infrastructure. Benchmarking applications are needed to compare the performance
across different edge deployments and against device-only and cloud-only
implementations. In this article, we present OpenRTiST, an open-source application
that is simultaneously compute-intensive, bandwidth-hungry, and latency-sensitive.
It implements a form of augmented reality that lets you “see the world through the eyes
of an artist.” We compare end-to-end application latency over varying network conditions
and measure performance across a variety of edge platforms. OpenRTiST is designed to
be easily deployed and has been used to showcase the benefits of edge computing.

OpenRTIST: End-to-End Benchmarking for Edge Computing By George, S., Eiszler, T., Iyengar, R., Turki, H., Feng, Z., Wang J., Pillai, P., Satyanarayanan, M. was published in IEEE Pervasive Computing, Volume 19, Issue 4, October-December 2020