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EmuFog : Extensible and scalable emulation of large-scale fog computing infrastructures

Title data

Mayer, Ruben ; Graser, Leon ; Gupta, Harshit ; Saurez, Enrique ; Ramachandran, Umakishore:
EmuFog : Extensible and scalable emulation of large-scale fog computing infrastructures.
In: 2017 IEEE Fog World Congress (FWC). - Piscataway, NJ : IEEE , 2017
ISBN 978-1-5386-3666-4
DOI: https://doi.org/10.1109/FWC.2017.8368525

Abstract in another language

The diversity of Fog Computing deployment models and the lack of publicly available Fog infrastructure makes the design of an efficient application or resource management policy a challenging task. Such research often requires a test framework that facilitates the experimental evaluation of an application or protocol design in a repeatable and controllable manner. In this paper, we present EmuFog - an extensible emulation framework tailored for Fog computing scenarios - that enables the from-scratch design of Fog Computing infrastructures and the emulation of real applications and workloads. EmuFog enables researchers to design the network topology according to the use-case, embed Fog Computing nodes in the topology and run Docker-based applications on those nodes connected by an emulated network. Each of the sub-modules of Emu Fog are easily extensible, although EmuFog provides a default implementation for each of them. The scalability and efficacy of EmuFog are evaluated both on synthetic and real-world network topologies.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems > Chair Data Systems - Univ.-Prof. Dr. Ruben Mayer
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 25 Apr 2023 13:29
Last Modified: 05 Feb 2024 07:40
URI: https://eref.uni-bayreuth.de/id/eprint/76025