Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture

Summary

This systematic review synthesises the state-of-the-art in distributed artificial intelligence (DAI) from 2016 to 2022, exploring technological enablers and applications for smart societies. The authors propose Imtidad, a framework and software reference architecture for provisioning DAI services across heterogeneous cloud, fog, and edge computing layers, alongside a future networking infrastructure transformation framework to support DAI deployment.

Regional applicability

This paper addresses general AI infrastructure and computing architecture rather than farming systems, soil health, or nutrition; it has limited direct applicability to UK agricultural or food systems research unless organisations are developing distributed AI applications for precision agriculture or food supply chain optimisation.

Key measures

Taxonomy of DAI aspects (AI workflow, distribution paradigms, supporting infrastructure, management techniques, applications); framework and reference architecture design; infrastructure transformation framework

Outcomes reported

The paper provides a comprehensive taxonomy and review of distributed AI literature (2016–2022), identifying opportunities and challenges in provisioning distributed AI as a service. It proposes the Imtidad framework and reference architecture for deploying DAI services across cloud, fog, and edge computing layers.

Topic tags