Caching in dynamic IoT networks by deep reinforcement learning

J Yao, N Ansari - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
… Note that our caching strategies in dynamic IoT networks can also be applied to mobile IoT
networks where the IoT devices are mobile if we assume that the IoT devices remain static …
被引用次数：37 相关文章 所有 2 个版本

Deep reinforcement learning for RIS-aided secure mobile edge computing in industrial internet of things

J Xu, A Xu, L Chen, Y Chen, X Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
… intensive and delay-sensitive industrial Internet of things (IIoT) applications. However, the …
propose a deep reinforcement learning (DRL)-based algorithm, where a deep deterministic …
被引用次数：8 相关文章

Blockchain-driven optimization of IoT in mobile edge computing environment with deep reinforcement learning and multi-criteria decision-making techniques

K Moghaddasi, M Masdari - Cluster Computing, 2023 - Springer
… ) presents complex challenges in task offloading, especially within Mobile Edge Computing
(… a Double Deep Q-Network (DDQN), a cutting-edge algorithm of Deep Reinforcement …
被引用次数：6 相关文章

Reinforcement learning for cost-effective IoT service caching at the edge

B Huang, X Liu, Y Xiang, D Yu, S Deng… - Journal of Parallel and …, 2022 - Elsevier
… networks as a Markov decision process, and then adopt a deep reinforcement learning
algorithm to solve this problem. Its main objective is to minimize the average data transmission …
被引用次数：10 相关文章 所有 4 个版本
[PDF] arxiv.org

Resource allocation for edge computing in IoT networks via reinforcement learning

X Liu, Z Qin, Y Gao - ICC 2019-2019 IEEE international …, 2019 - ieeexplore.ieee.org
… 1, we consider an IoT network with many end devices (ie, IoT devices) and a gateway (ie, the
edge … Bennis, “Performance optimization in mobile-edge computing via deep reinforcement …
被引用次数：109 相关文章 所有 5 个版本

C-fdrl: Context-aware privacy-preserving offloading through federated deep reinforcement learning in cloud-enabled IoT

Y Xu, MZA Bhuiyan, T Wang, X Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
… 1) We propose C-fDRL, a novel context-aware task offloading in cloud-edge-assisted IoT.
We provide the detailed design and architecture of the C-fDRL. 2) We define context-aware …
被引用次数：41 相关文章

Dynamic service function chain orchestration for NFV/MEC-enabled IoT networks: A deep reinforcement learning approach

Y Liu, H Lu, X Li, Y Zhang, L Xi… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
… That is to say, the edge clouds can combine with the remote core cloud to provide services
and computing capacities to edge IoT devices located at the edge of the mobile networks. …
被引用次数：63 相关文章
[PDF] arxiv.org

When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense …

S Yu, X Chen, Z Zhou, X Gong… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
… edge devices and their serving edge servers, especially in the 5G ultradense network (UDN)
scenarios. Ultradense edge … a novel two-timescale deep reinforcement learning (2Ts-DRL) …
被引用次数：278 相关文章 所有 4 个版本

Qoe-guaranteed distributed offloading decision via partially observable deep reinforcement learning for edge-enabled internet of things

J Hou, Y Wu, J Cai, Z Zhou - Neural Computing and Applications, 2023 - Springer
… of edge-enabled IoT. Additionally, existing methods often overlook the heterogeneity of IoT
tasks generated by various IoT devices, … IoT tasks offloading in distributed edge-enabled IoT …
被引用次数：3 相关文章 所有 2 个版本

Service function chain embedding for NFV-enabled IoT based on deep reinforcement learning

X Fu, FR Yu, J Wang, Q Qi, J Liao - IEEE Communications …, 2019 - ieeexplore.ieee.org
… to deep reinforcement learning (DRL) [7], we present a DRL-based SFC embedding scheme
in NFV-enabled IoT. … include edge computing, IoT, ubiquitous services, and deep learning. …
被引用次数：67 相关文章 所有 2 个版本