Experimenting an Edge-Cloud Computing Model on the GPULab Fed4Fire Testbed

Authors

Vikas Tomer, Graphic Era Deemed to be University
Sachin Sharma, Technological University DublinFollow

Author ORCID Identifier

https://orcid.org/0000-0002-8358-2258

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Information Science

Publication Details

IEEE LANMAN 2022

Abstract

There are various open testbeds available for testing algorithms and prototypes, including the Fed4Fire testbeds. This demo paper illustrates how the GPULAB Fed4Fire testbed can be used to test an edge-cloud model that employs an ensemble machine learning algorithm for detecting attacks on the Internet of Things (IoT). We compare experimentation times and other performance metrics of our model based on different characteristics of the testbed, such as GPU model, CPU speed, and memory. Our goal is to demonstrate how an edge-computing model can be run on the GPULab testbed. Results indicate that this use case can be deployed seamlessly on the GPULAB testbed.

DOI

https://doi.org/10.1109/LANMAN54755.2022.9820006

Recommended Citation

V. Tomer and S. Sharma, "Experimenting an Edge-Cloud Computing Model on the GPULab Fed4Fire Testbed," 2022 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), 2022, pp. 1-2, doi: 10.1109/LANMAN54755.2022.9820006.

Funder

NGIAtlantic H2020 project under agreement no. OC3-292

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.