RL-Planner: Reinforcement Learning-Enabled Efficient Path Planning in Multi-UAV MEC Systems-Reference-Cited by-同舟云学术

RL-Planner: Reinforcement Learning-Enabled Efficient Path Planning in Multi-UAV MEC Systems

Published:2024-06 Issue:3 Volume:21 Page:3317-3329
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Ejaz Muhammad¹^ORCID,Gui Jinsong¹^ORCID,Asim Muhammad²^ORCID,El-Affendi Mohammed A.³^ORCID,Fung Carol⁴^ORCID,Abd El-Latif Ahmed A.³^ORCID

Affiliation:

1. School of Computer Science and Engineering, Central South University, Changsha, China

2. EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

3. EIAS Data Science Lab, College of Computer and Information Sciences, and the Center of Excellence in Quantum and Intelligent Computing, Prince Sultan University, Riyadh, Saudi Arabia

4. Gina Cody School of Engineering and Computer Science Montreal, Concordia University, Montreal, QC, Canada

Funder

EIAS Data Science Lab, College of Computer and Information Sciences, and Center of Excellence in Quantum and Intelligent Computing, Prince Sultan University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4275028/10599562/10477262.pdf?arnumber=10477262

Reference37 articles.

1. Energy Consumption and Sustainable Services in Intelligent Reflecting Surface and Unmanned Aerial Vehicles-Assisted MEC System for Large-Scale Internet of Things Devices

2. Multi-IRS and Multi-UAV-Assisted MEC System for 5G/6G Networks: Efficient Joint Trajectory Optimization and Passive Beamforming Framework

3. Interference-aware Game-theoretic Device Allocation for Mobile Edge Computing

4. Demand Response in NOMA-based Mobile Edge Computing: A Two-phase Game-theoretical Approach

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1. Comparison of Reinforcement Learning Algorithms for Edge Computing Applications Deployed by Serverless Technologies;Algorithms;2024-07-23

2. Energy efficient resource allocation of IRS-Assisted UAV network;Electronic Research Archive;2024