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 editorsKotilainen, Pyry; Mäkitalo, Niko; Systä, Kari; Mehraj, Ali; Waseem, Muhammad; Mikkonen, Tommi; Murillo, Juan Manuel

Journal or seriesJournal of Systems and Software

ISSN0164-1212

eISSN1873-1228

Publication year2025

Publication date10/01/2025

Volume222

Article number112333

PublisherElsevier

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1016/j.jss.2025.112333

Publication open accessOpenly available

Publication channel open accessPartially 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.


KeywordsInternet of thingscloud servicesartificial intelligenceethicsprivacy

Free keywordsInternet of Things; IoT; cloud computing; model cards; ethical orchestration; orchestration; artificial intelligence; AI; ethics; compliance; privacy; AI regulation


Contributing organizations


Related projects


Ministry reportingYes

VIRTA submission year2025

Preliminary JUFO rating3


Last updated on 2025-04-02 at 10:09