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Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks
Special Feature on Coordination of Networking and Computing: Architecture, Theory, and Practice | Updated：2024-06-03
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    • Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks

      Enhanced Publication
    • 图神经网络与深度强化学习结合的算力网络资源分配方法
    • “In the realm of computing force networks, a new research breakthrough has been achieved. Experts have developed a graph neural network-based deep reinforcement learning framework that optimizes network resources and computing resources. This innovation offers a solution to the challenges posed by the dynamic nature of network topologies, significantly advancing the field of network optimization.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 25, Issue 5, Pages: 701-712(2024)

    • DOI：10.1631/FITEE.2300009    

      CLC： TP393

    • Published：0 May 2024，

      Received：05 January 2023，

      Accepted：2023-04-24

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  • XUEYING HAN, MINGXI XIE, KE YU, et al. Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks. [J]. Frontiers of information technology & electronic engineering, 2024, 25(5): 701-712. DOI： 10.1631/FITEE.2300009.

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