Task Scheduling in Edge Computing Environments: a Hierarchical Cluster-based Federated Deep Reinforcement Learning Approach

Alsalem, L. and Djemame, K. orcid.org/0000-0001-5811-5263 (Accepted: 2025) Task Scheduling in Edge Computing Environments: a Hierarchical Cluster-based Federated Deep Reinforcement Learning Approach. In: UCC '25: Proceedings of the 18th IEEE/ACM International Conference on Utility and Cloud Computing. 2025 IEEE/ACM 18th International Conference on Utility and Cloud Computing, 01-04 Dec 2025, Nantes, France. ACM. (In Press)

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Item Type: Proceedings Paper
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This is an author produced version of a conference paper accepted for publication in UCC '25: Proceedings of the 18th IEEE/ACM International Conference on Utility and Cloud Computing, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.
Dates:
  • Accepted: 11 October 2025
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Date Deposited: 20 Nov 2025 15:36
Last Modified: 20 Nov 2025 15:36
Status: In Press
Publisher: ACM
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