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OpenRTiST: End-to-End Benchmarking for Edge Computing.
- Source :
- IEEE Pervasive Computing; Oct-Dec2020, Vol. 19 Issue 4, p10-18, 9p
- Publication Year :
- 2020
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- EDGE computing
GRAPHICS processing units
Subjects
Details
- Language :
- English
- ISSN :
- 15361268
- Volume :
- 19
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Pervasive Computing
- Publication Type :
- Academic Journal
- Accession number :
- 147134005
- Full Text :
- https://doi.org/10.1109/MPRV.2020.3028781