Federated and Distributed Intelligence for Sustainable Edge-Cloud Ecosystems
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "AI Systems: Theory and Applications".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 102
Special Issue Editors
Interests: federated learning; edge–cloud computing; distributed AI; IoT/IoV; sustainable AI; smart cities
Interests: hierarchical federated learning; security in energy management systems; privacy-preserving green IoT; adversarial AI for smart cities; threat detection in edge–cloud ecosystems
Interests: green edge computing architectures; sustainable IoT paradigms; high-performance computing for urban sustainability; cloud-to-edge orchestration; smart city services
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid expansion of edge–cloud ecosystems, IoT infrastructures, and AI-driven services is creating unprecedented pressure on energy consumption, data governance, and environmental sustainability. Federated and distributed intelligence have emerged as key paradigms to address these challenges by enabling decentralized, energy-aware, and privacy-preserving learning.
This Special Issue explores how decentralized AI methods can support sustainable digital infrastructures, aligning with SDG 9, 11, and 13. Crucially, we move beyond traditional performance metrics to emphasize the trade-offs between model accuracy and environmental impact. We welcome contributions that quantify energy consumption (carbon footprint), propose lightweight communication protocols, or demonstrate energy-efficient orchestration.
Research topics include the following: federated learning and distributed optimization; energy-efficient edge–cloud orchestration; sustainable IoT/IoV systems; privacy-preserving data governance; distributed situational awareness for smart cities; and frameworks for assessing the environmental footprint of distributed AI.
Both original research articles and reviews are welcome.
Dr. Francisco A. Pujol
Dr. Amir Javed
Prof. Dr. Higinio Mora
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- federated learning
- distributed intelligence
- sustainable edge–cloud computing
- green federated learning
- green IoT and IoV
- privacy-preserving machine learning
- smart cities and mobility
- carbon-aware computing
- edge intelligence
- resource-constrained AI
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