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Hierarchical RL for Load Balancing and QoS Management in Multi-Access Networks

机译:用于负载平衡的分层RL和多接入网络中的QoS管理

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摘要

This paper deals with the problem of resource management in Multi-Access Networks. A Reinforcement Learning based hierarchical control strategy is presented. The main contribution of the proposed approach is its capability of simultaneously tacking the load balancing and QoS management problems in a scalable, dynamic and closed-loop way. The effectiveness of the proposed solution has been proved in a specific case study in the context of which the performances of the proposed algorithm have been compared with a standard load balancing controller.
机译:本文涉及多接入网络资源管理问题。 提出了一种基于加强学习的分层控制策略。 所提出的方法的主要贡献是其能够以可扩展,动态和闭环的方式同时加以负载平衡和QoS管理问题。 在该上下文中已经证明了所提出的解决方案的有效性,其中已经将所提出的算法的性能与标准负载平衡控制器进行比较。

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