A Deep Reinforcement Learning Approach for Improving Age of Information in Mission-Critical IoT

Author:

Farag Hossam1,Gidlund Mikael2,Stefanovic Cedomir1

Affiliation:

1. Aalborg University,Department of Electronic Systems,Copenhagen,Denmark

2. Mid Sweden University,Department of Information Systems and Technology,Sundsvall,Sweden

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing Real-Time Decision-Making in Sensor Networks;2023 16th International Conference on Developments in eSystems Engineering (DeSE);2023-12-18

2. AA-DL: AoI-Aware Deep Learning Approach for D2D-Assisted Industrial IoT;2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT);2023-12-10

3. Timely and Efficient Information Delivery in Real-Time Industrial IoT Networks;2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC);2023-09-05

4. Enabling Communication and Networking Technologies for 6G in Healthcare Sector;2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon);2023-08-18

5. Reinforcement Learning for Optimizing Age of Information and Energy Consumption in Misson-critical IoT;2023 International Conference on Communications, Computing and Artificial Intelligence (CCCAI);2023-06

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