Graph Tasks Offloading and Resource Allocation in Multi-Access Edge Computing: A DRL-and-Optimization-Aided Approach
Author:
Affiliation:
1. Sun Yat-sen University, Guangzhou, China
2. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China
Funder
National Key R&D Program of China
National Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/6488902/6930788/10114596.pdf?arnumber=10114596
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1. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;Proc 35th Int Conf Mach Learn,0
2. The Complexity Analysis of an Efficient Interior-Point Algorithm for Linear Optimization
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4. Intelligent Service Deployment Policy for Next-Generation Industrial Edge Networks
5. Offloading in Mobile Edge Computing: Task Allocation and Computational Frequency Scaling
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1. Cost-aware task offloading in vehicular edge computing: A Stackelberg game approach;Vehicular Communications;2024-10
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3. Deep reinforcement learning‐based resource allocation in multi‐access edge computing;Concurrency and Computation: Practice and Experience;2023-12-22
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