In this paper, we present Federated learning-based dynamic Cache allocation (FedCache) for edge caches in dynamic, constrained networks. FedCache uses federated learning to learn the benefit of a particular cache allocation with low communication overhead. Edge nodes learn locally to adapt to ...
FedICT: Federated Multi-task Distillation for Multi-access Edge Computing. IEEE Transactions on Parallel and Distributed Systems (TPDS). 2024 Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration. IEEE International Conference on Computer Communications (INFOCOM)....
Federated learning empowered mobility-aware proactive content offloading framework for fog radio access networks 2022, Future Generation Computer Systems Show abstract Air Computing: A Survey on a New Generation Computation Paradigm in 6G Wireless Networks 2022, arXivRecommended...
Sasikala, Learning based latency minimization techniques in mobile edge computing (mec) systems: A comprehensive survey, in: 2021 International conference on system, computation, automation and networking (ICSCAN), IEEE, 2021, pp. 1–6. Google Scholar [8] H. Ahlehagh, S. Dey, Video-aware ...
In one embodiment, the storage of a particular object into deeper storage allows for the “sharing” of that object on a much larger scale (e.g., between different computing systems or application servers). For example, an object commonly used by a cluster of application servers may be ...
In local caching-based systems, the end-users do not have any information about the cached data items, and they do not know where to send the requests to fetch the desired data items. Therefore, Recommendation-based Q Learning (RQL) algorithms are most suitable to enhance system efficiency [...
Resource-aware multi-task offloading and dependency-aware scheduling for integrated edge-enabled IoV 2023, Journal of Systems Architecture Citation Excerpt : This technology supports various kinds of communication patterns, for example, Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehi...
Joint Resource Allocation and Learning Optimization for UAV-Assisted Federated Learning. Appl. Sci. 2023, 13, 3771. [CrossRef] 13. Wu, H.; Chen, J.; Lyu, F.; Wang, L.; Shen, X. Joint Caching and Trajectory Design for Cache-Enabled UAV in Vehicular Networks. In Proceedings of the ...