Toward Optimal Resource Allocation: A Multi-Agent DRL Based Task Offloading Approach in Multi-UAV-Assisted MEC Networks-Reference-Cited by-同舟云学术

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Toward Optimal Resource Allocation: A Multi-Agent DRL Based Task Offloading Approach in Multi-UAV-Assisted MEC Networks

Published:2024 Issue: Volume:12 Page:81428-81440
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tariq Muhammad Naqqash¹^ORCID,Wang Jingyu¹,Raza Salman²^ORCID,Siraj Mohammad³^ORCID,Altamimi Majid³^ORCID,Memon Saifullah⁴^ORCID

Affiliation:

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

2. Department of Computer Science, National Textile University, Faisalabad, Pakistan

3. Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia

4. Department of Information Technology, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, Pakistan

Funder

Deputyship for Research and Innovation, 433 Ministry of Education, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10551824.pdf?arnumber=10551824

Reference29 articles.

1. A Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions

2. An efficient task offloading scheme in vehicular edge computing

3. Joint Task Offloading and Resource Allocation in UAV-Enabled Mobile Edge Computing

4. MCLA Task Offloading Framework for 5G-NR-V2X-Based Heterogeneous VECNs

5. DRL-driven zero-RIS assisted energy-efficient task offloading in vehicular edge computing networks

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