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On a Fog Computing Platform Built on ARM Architectures by Docker Container Technology
Eiermann, Andreas; Renner, Mathias; Großmann, Marcel; u. a. (2026): On a Fog Computing Platform Built on ARM Architectures by Docker Container Technology, in: Bamberg: Otto-Friedrich-Universität, S. 71–86.
Faculty/Chair:
Author:
Publisher Information:
Year of publication:
2026
Pages:
Series ; Volume:
Communications in Computer and Information Science
Source/Other editions:
Gerald Eichler, Christian Erfurth, und Günter Fahrnberger (Hrsg.), Innovations for Community Services : 17th International Conference, I4CS 2017, Darmstadt, Germany, June 26-28, 2017, Proceedings, Cham: Springer International Publishing, 2017, S. 71–86, ISBN: 978-3-319-60446-6, 978-3-319-60447-3
Year of first publication:
2017
Language:
English
Licence:
Abstract:
Fog computing constitutes currently a challenging effort to establish the concepts and services of cloud computing at the edge of converging wireless networks and wired high-speed backbones. We discuss the concepts of our fog computing platform HCL-BaFog. It is built on top of Hypriot Cluster Lab (HCL) which has been developed by the Hypriot Pirate Crew in recent years based on single board computers with an ARM architecture. It uses LINUX container technology as underlying open source platform that has been established by means of the rapidly evolving framework Docker. We present the design principles of our fog computing platform and discuss its different software components. To create clusters of fog cells subject to high-availability requirements and to provide failsafe data processing, we further summarize some performance results on the integration of the orchestration tools Docker Swarm Mode and Kubernetes on HCL and draw some conclusions regarding their suitability for fog computing.
Keywords: ; ; ; ; ; ;
Fog computing
Hypriot Cluster Lab
ARM architecture
Container virtualization
Docker Swarm Mode
Kubernetes
High-availability
Type:
Conferenceobject
Activation date:
April 27, 2026
Permalink
https://fis.uni-bamberg.de/handle/uniba/114835