Výsledky vyhledávání - "Deng, Xiaofang"

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An Intelligent SDWN Routing Algorithm Based on Network Situational Awareness and Deep Reinforcement Learning

Autor: Li, Jinqiang, Ye, Miao, Huang, Linqiang, Deng, Xiaofang, Qiu, Hongbing, Wang, Yong

Due to the highly dynamic changes in wireless network topologies, efficiently obtaining network status information and flexibly forwarding data to improve communication quality of service are important challenges. This article introduces an intellige

Externí odkaz: http://arxiv.org/abs/2305.10441

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Intelligent multicast routing method based on multi-agent deep reinforcement learning in SDWN

Autor: Hu, Hongwen, Ye, Miao, Zhao, Chenwei, Jiang, Qiuxiang, Wang, Yong, Qiu, Hongbing, Deng, Xiaofang

Multicast communication technology is widely applied in wireless environments with a high device density. Traditional wireless network architectures have difficulty flexibly obtaining and maintaining global network state information and cannot quickl

Externí odkaz: http://arxiv.org/abs/2305.10440

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A New Intelligent Cross-Domain Routing Method in SDN Based on a Proposed Multiagent Reinforcement Learning Algorithm

Autor: Ye, Miao, Huang, Linqiang, Deng, Xiaofang, Wang, Yong, Jiang, Qiuxiang, Qiu, Hongbing, Wen, Peng

Message transmission and message synchronization for multicontroller interdomain routing in software-defined networking (SDN) have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing met

Externí odkaz: http://arxiv.org/abs/2303.07572

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A Novel Anomaly Detection Method for Multimodal WSN Data Flow via a Dynamic Graph Neural Network

Autor: Zhang, Qinghao, Ye, Miao, Qiu, Hongbing, Wang, Yong, Deng, Xiaofang

Anomaly detection is widely used to distinguish system anomalies by analyzing the temporal and spatial features of wireless sensor network (WSN) data streams; it is one of critical technique that ensures the reliability of WSNs. Currently, graph neur

Externí odkaz: http://arxiv.org/abs/2202.10454

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