Title
The Two Faces of AI in Green Mobile Computing: A Literature Review
Author
Siemers, Wander (Student TU Delft)
Sallou, J. (TU Delft Software Engineering) ![ORCID 0000-0003-2230-9351 ORCID 0000-0003-2230-9351](/sites/all/themes/tud_repo3/img/icons/orcid_16x16.png)
Cruz, Luis (TU Delft Software Engineering) ![ORCID 0000-0002-1615-355X ORCID 0000-0002-1615-355X](/sites/all/themes/tud_repo3/img/icons/orcid_16x16.png)
Contributor
Ceballos, Cristina (editor)
Date
2023
Abstract
Artificial intelligence is bringing ever new functionalities to the realm of mobile devices that are now considered essential (e.g., camera and voice assistants, recommender systems). Yet, operating artificial intelligence takes up a substantial amount of energy. However, artificial intelligence is also being used to enable more energy-efficient solutions for mobile systems. Hence, artificial intelligence has two faces in that regard, it is both a key enabler of desired (efficient) mobile functionalities and a major power draw on these devices, playing a part in both the solution and the problem. In this paper, we present a review of the literature of the past decade on the usage of artificial intelligence within the realm of green mobile computing. From the analysis of 34 papers, we highlight the emerging patterns and map the field into 13 main topics that are summarized in details. Our results showcase that the field is slowly increasing in the past years, more specifically, since 2019. Regarding the double impact AI has on the mobile energy consumption, the energy consumption of AI-based mobile systems is under-studied in comparison to the usage of AI for energy-efficient mobile computing, and we argue for more exploratory studies in that direction. We observe that although most studies are framed as solution papers (94%), the large majority do not make those solutions publicly available to the community. Moreover, we also show that most contributions are purely academic (28 out of 34 papers) and that we need to promote the involvement of the mobile software industry in this field.
Subject
mobile software
energy consumption
artificial intelligence
To reference this document use:
http://resolver.tudelft.nl/uuid:77d316a3-d919-4231-9510-a94839be92be
DOI
https://doi.org/10.1109/SEAA60479.2023.00053
Publisher
IEEE, Piscataway
Embargo date
2024-07-01
ISBN
979-8-3503-4236-9
Source
Proceedings of the 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Event
2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2023-09-06 → 2023-09-08, Durres, Albania
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2023 Wander Siemers, J. Sallou, Luis Cruz