Algorithm for resource allocation and computing offloading in 6G networks: deep reinforcement learning-based
The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G netw...
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| Main Authors: | , , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
IEEE
2024
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/114447/1/114447_Algorithm%20for%20resource%20allocation.pdf http://irep.iium.edu.my/114447/ https://ieeexplore.ieee.org/document/10652281 |
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| Summary: | The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G networks. The algorithm leverages the power of deep reinforcement learning to dynamically determine the optimal computing offloading decisions and resource allocation strategies. The Deep Reinforcement Learning-based DCORA algorithm for computation offloading and resource allocation is effective, as demonstrated by our simulations. When compared directly, the suggested DCORA algorithm performs 15% better than other baseline systems. |
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