Deep Reinforcement Learning and Game Theory for Computation Offloading in Dynamic Edge Computing Markets

Deep Reinforcement Learning and Game Theory for Computation Offloading in Dynamic Edge Computing Markets

As a promising paradigm, computation offloading technology can offload computing tasks to multi-access edge computing (MEC) servers, which is an appealing choice for resource-constrained terminal devices to reduce their computational effort. However, due to limited resources, one crucial research ch...

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Bibliographic Details
Main Authors: Shuyang Li, Xiaohui Hu, Yongwen Du
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Edge computing
offloading decision
Markov decision process
deep reinforcement learning
game theory
Nash equilibrium
Online Access:https://ieeexplore.ieee.org/document/9525401/

Internet

https://ieeexplore.ieee.org/document/9525401/

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