Fractional deep reinforcement learning for age-minimal mobile edge computing

[PDF] arxiv.org

Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories

N Yang, S Chen, H Zhang… - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) broadens the scope of computation and storage beyond the
central network, incorporating edge nodes close to end devices. This expansion facilitates …
被引用次数：4 相关文章 所有 3 个版本

Age-minimal CPU scheduling

M Zhou, M Zhang, HH Yang… - IEEE INFOCOM 2024 …, 2024 - ieeexplore.ieee.org
The proliferation of real-time status updating applications and ubiquitous mobile devices
have motivated the analysis and optimization of data freshness in the context of age of …
被引用次数：1 相关文章
[PDF] arxiv.org

Asynchronous Fractional Multi-Agent Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing

L Jin, M Tang, J Pan, M Zhang, H Wang - arXiv preprint arXiv:2409.16832, 2024 - arxiv.org
In the realm of emerging real-time networked applications like cyber-physical systems
(CPS), the Age of Information (AoI) has merged as a pivotal metric for evaluating the …
相关文章 所有 2 个版本