Deep reinforcement learning-based V2V partial computation offloading in vehicular fog computing

[PDF] arxiv.org

A review of resource management in fog computing: Machine learning perspective

M Fahimullah, S Ahvar, M Trocan - arXiv preprint arXiv:2209.03066, 2022 - arxiv.org
Fog computing becomes a promising technology to process user's requests near the
proximity of users to reduce response time for latency-sensitive requests. Despite its …
被引用次数：9 相关文章 所有 2 个版本

Fast adaptive task offloading and resource allocation via multiagent reinforcement learning in heterogeneous vehicular fog computing

Z Gao, L Yang, Y Dai - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
In vehicular fog computing, task offloading enables mobile vehicles (MVs) to offer ultralow
latency services for computation-intensive tasks. Nevertheless, the edge server (ES) may …
被引用次数：13 相关文章

SAC-based Computation Offloading and Resource Allocation in Vehicular Edge Computing

Y Zheng, H Zhou, R Chen, K Jiang… - IEEE INFOCOM 2022 …, 2022 - ieeexplore.ieee.org
The Vehicular Edge Computing (VEC) provides powerful computing resources for intelligent
terminals. However, the diversity of computing resources at edge nodes (ie, edge servers …
被引用次数：5 相关文章

QoS-Aware Computational Resource Allocation

J Du, C Jiang - Cooperation and Integration in 6G Heterogeneous …, 2022 - Springer
Recently, the boosting growth of computation-heavy applications raises great challenges for
the Fifth Generation (5G) and future wireless networks. As responding, the hybrid edge and …
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Dynamic Uplink and Downlink Resource Allocation using Deep RI Learning Approach in 5G-HetNets

V Pawar, A Sharma - 2022 Second International Conference on …, 2022 - ieeexplore.ieee.org
To anticipate the continuously shifting traffic and channel state and to adjust the TDD config
on the spot in a high-mobility environment, a novel strategy is required. In order to flexibly …
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