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Fog vs. Cloud Computing: Should I Stay or Should I Go?

Institute of Computing, University of Campinas, Campinas 13083-852, Brazil
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This paper is an extended version of “Pisani, F.; Borin, E. Fog vs. Cloud Computing: Should I Stay or Should I Go?” published in Proceedings of the INTelligent Embedded Systems Architectures and Applications (INTESA), Turin, Italy, 4 October 2018; ACM: New York, NY, USA, 2018; pp. 27–32, doi:10.1145/3285017.3285026.
Future Internet 2019, 11(2), 34; https://doi.org/10.3390/fi11020034
Received: 1 December 2018 / Revised: 31 December 2018 / Accepted: 11 January 2019 / Published: 2 February 2019
(This article belongs to the Special Issue Selelcted papers from INTESA Workshop 2018)
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Abstract

In this article, we work toward the answer to the question “is it worth processing a data stream on the device that collected it or should we send it somewhere else?”. As it is often the case in computer science, the response is “it depends”. To find out the cases where it is more profitable to stay in the device (which is part of the fog) or to go to a different one (for example, a device in the cloud), we propose two models that intend to help the user evaluate the cost of performing a certain computation on the fog or sending all the data to be handled by the cloud. In our generic mathematical model, the user can define a cost type (e.g., number of instructions, execution time, energy consumption) and plug in values to analyze test cases. As filters have a very important role in the future of the Internet of Things and can be implemented as lightweight programs capable of running on resource-constrained devices, this kind of procedure is the main focus of our study. Furthermore, our visual model guides the user in their decision by aiding the visualization of the proposed linear equations and their slope, which allows them to find if either fog or cloud computing is more profitable for their specific scenario. We validated our models by analyzing four benchmark instances (two applications using two different sets of parameters each) being executed on five datasets. We use execution time and energy consumption as the cost types for this investigation. View Full-Text
Keywords: fog computing; cloud computing; IoT; processing cost trade-off; platform modeling; resource-constrained devices fog computing; cloud computing; IoT; processing cost trade-off; platform modeling; resource-constrained devices
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Pisani, F.; Martins do Rosario, V.; Borin, E. Fog vs. Cloud Computing: Should I Stay or Should I Go? Future Internet 2019, 11, 34.

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