A1 Journal article (refereed)
Allocating distributed AI/ML applications to cloud-edge continuum based on privacy, regulatory, and ethical constraints (2025)
Kotilainen, P., Mäkitalo, N., Systä, K., Mehraj, A., Waseem, M., Mikkonen, T., & Murillo, J. M. (2025). Allocating distributed AI/ML applications to cloud-edge continuum based on privacy, regulatory, and ethical constraints. Journal of Systems and Software, 222, Article 112333. https://doi.org/10.1016/j.jss.2025.112333
JYU authors or editors
Publication details
All authors or editors: Kotilainen, Pyry; Mäkitalo, Niko; Systä, Kari; Mehraj, Ali; Waseem, Muhammad; Mikkonen, Tommi; Murillo, Juan Manuel
Journal or series: Journal of Systems and Software
ISSN: 0164-1212
eISSN: 1873-1228
Publication year: 2025
Publication date: 10/01/2025
Volume: 222
Article number: 112333
Publisher: Elsevier
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1016/j.jss.2025.112333
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/99941
Abstract
There is an increasing need for practitioners to address legislative and ethical issues in both the development and deployment of data-driven applications with AI/ML due to growing concerns and regulations, such as GDPR and the EU AI Act. Thus, the field needs a systematic framework for assessing risks and helping to stay compliant with regulations in designing and deploying software systems. Clear and concise descriptions of risks associated with each model and data source are needed to guide the design without acquiring deep knowledge of the regulations. In this paper, we propose a reference architecture for an ethical orchestration system that manages distributed AI/ML applications on the cloud–edge continuum and present a proof-of-concept implementation of the main ideas of the architecture. Our starting point is the methods already in use in the industry, such as model cards, and we extend the idea of model cards to data source cards and software component cards, which provide practitioners and the automated system with relevant information in actionable form. With the metadata card based orchestration system and information about the risk levels of the target infrastructure, the users can create deployments of distributed AI/ML systems that fulfill the regulatory and other requirements.
Keywords: Internet of things; cloud services; artificial intelligence; ethics; privacy
Free keywords: Internet of Things; IoT; cloud computing; model cards; ethical orchestration; orchestration; artificial intelligence; AI; ethics; compliance; privacy; AI regulation
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Ministry reporting: Yes
VIRTA submission year: 2025
Preliminary JUFO rating: 3