Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing

Deep Reinforcement Learning With Dueling DQN for Partial Computation Offloading and Resource Allocation in Mobile Edge Computing

Computation offloading transfers resource-intensive tasks from local Internet of Things (IoT) devices to powerful edge servers, which minimizes latency and reduces the computational load on IoT devices. Deep Reinforcement Learning (DRL) is widely utilized to optimize computation offloading decisions...

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Bibliographic Details
Main Authors: Ehzaz Mustafa, Junaid Shuja, Faisal Rehman, Abdallah Namoun, Mazhar Ali, Abdullah Alourani
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Computation offloading
deep Q network (DQN)
edge computing
Internet of Things (IoT)
resource allocation
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/11015773/
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https://ieeexplore.ieee.org/document/11015773/

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