Deep Reinforcement Learning Based Resource Allocation Method in Future Wireless Networks with Blockchain Assisted MEC Network-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning Based Resource Allocation Method in Future Wireless Networks with Blockchain Assisted MEC Network

Published:2024-06-04 Issue: Volume: Page:289-294
ISSN:
Container-title:2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)
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Author:

Consul Prakhar¹,Budhiraja Ishan¹,Garg Deepak²,Sharma Sachin³,Muthanna Ammar⁴

Affiliation:

1. Bennett University,School of Computer Science Engineering & Technology,Greater Noida,Uttar Pradesh,India

2. SR University,School of Computer Science and Artificial Intelligence,Warangal,Telangana,India

3. State Bank of India,Panchkula,Chandigarh,India

4. Peoples Friendship University of Russia, RUDN University,Moscow,Russia,117198

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10579075/10579079/10579228.pdf?arnumber=10579228

Reference20 articles.

1. ChainFL: A Simulation Platform for Joint Federated Learning and Blockchain in Edge/Cloud Computing Environments

2. A Hybrid Task Offloading and Resource Allocation Approach for Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning for Future Wireless Network

3. Blockchain and Semi-Distributed Learning-Based Secure and Low-Latency Computation Offloading in Space-Air-Ground-Integrated Power IoT

4. When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multitimescale Resource Management for Multiaccess Edge Computing in 5G Ultradense Network

5. Power Allocation Scheme Based on DRL for CF Massive MIMO Network with UAV

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