Optimization-driven Deep Reinforcement Learning for Sniffer Patrolling in Wireless Networks-Reference-Cited by-同舟云学术

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Optimization-driven Deep Reinforcement Learning for Sniffer Patrolling in Wireless Networks

Published:2022-05-30 Issue: Volume: Page:
ISSN:
Container-title:2022 International Wireless Communications and Mobile Computing (IWCMC)
language:
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Author:

Luo Xiaoling¹,Wang Meng²,Zeng Chunnian¹,Li Chengtao³,Xu Jing⁴,Gong Shimin²

Affiliation:

1. School of Information Engineering, Wuhan University of Technology,China

2. School of Intelligent Systems Engineering, Sun Yat-sen University,China

3. China Three Gorges Corporation,China

4. School of Electronic Information and Communications, Huazhong University of Science and Technology,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9823957/9824097/09824956.pdf?arnumber=9824956

Reference16 articles.

1. Toward Optimal Distributed Monitoring of Multi-Channel Wireless Networks

2. Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

3. Taking the Human Out of the Loop: A Review of Bayesian Optimization

4. UAV-relay Placement with Unknown User Locations and Channel Parameters

Cited by 1 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. Dense Multi-Channel Sniffing in Large IoT Networks;IEEE Access;2022

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