Edge to cloud tools: A Multivocal Literature Review
Moreschini, Sergio; Younesian, Elham; Hästbacka, David; Albano, Michele; Hošek, Jiří; Taibi, Davide (2024-01-11)
Elsevier
11.01.2024
Sergio Moreschini, Elham Younesian, David Hästbacka, Michele Albano, Jiří Hošek, Davide Taibi, Edge to cloud tools: A Multivocal Literature Review, Journal of Systems and Software, Volume 210, 2024, 111942, ISSN 0164-1212, https://doi.org/10.1016/j.jss.2023.111942
https://creativecommons.org/licenses/by/4.0/
© 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
https://creativecommons.org/licenses/by/4.0/
© 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202402121712
https://urn.fi/URN:NBN:fi:oulu-202402121712
Tiivistelmä
Abstract
Edge-to-cloud computing is an emerging paradigm for distributing computational tasks between edge devices and cloud resources. Different approaches for orchestration, offloading, and many more purposes have been introduced in research. However, it is still not clear what has been implemented in the industry. This work aims to merge this gap by mapping the existing knowledge on edge-to-cloud tools by providing an overview of the current state of research in this area and identifying research gaps and challenges. For this purpose, we conducted a Multivocal Literature Review (MLR) by analyzing 40 tools from 1073 primary studies (220 PS from the white literature and 853 PS from the grey literature). We categorized the tools based on their characteristics and targeted environments. Overall, this systematic mapping study provides a comprehensive overview of edge-to-cloud tools and highlights several opportunities for researchers and practitioners for future research in this area.
Edge-to-cloud computing is an emerging paradigm for distributing computational tasks between edge devices and cloud resources. Different approaches for orchestration, offloading, and many more purposes have been introduced in research. However, it is still not clear what has been implemented in the industry. This work aims to merge this gap by mapping the existing knowledge on edge-to-cloud tools by providing an overview of the current state of research in this area and identifying research gaps and challenges. For this purpose, we conducted a Multivocal Literature Review (MLR) by analyzing 40 tools from 1073 primary studies (220 PS from the white literature and 853 PS from the grey literature). We categorized the tools based on their characteristics and targeted environments. Overall, this systematic mapping study provides a comprehensive overview of edge-to-cloud tools and highlights several opportunities for researchers and practitioners for future research in this area.
Kokoelmat
- Avoin saatavuus [38840]
Ellei muuten mainita, aineiston lisenssi on https://creativecommons.org/licenses/by/4.0/