Deep Learning, Deep Reinforcement Learning for Computer Networking
This special issue belongs to the section "Sensor Networks".
Special Issue Information
Dear Colleagues,
Over the last decade, there has been a great development in deep learning, which is considered as a promising technology for diverse areas including computer networking. Despite a considerable amount of efforts, applying deep learning technology to computer networking is still at an early stage. For instance, using deep learning to control network resources where multiple heterogeneous networks co-exist has been poorly studied. Additionally, the limitation of deep learning in networking due to lack of available network data has not been sufficiently addressed. Moreover, the high time and space complexity problem of deep reinforcement learning, which is another important research direction of intelligent network control, remains as a major challenge.Through this Special Issue, we aim at assembling high-quality research papers on deep learning and deep reinforcement learning-based computer networking. The Special Issue will be an open platform for researchers to share pioneering ideas and studies.
Prof. Dr. Seokhoon Yoon
Guest Editor
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Keywords
- Deep learning, deep reinforcement learning for network fault detection and prediction
- Deep learning, deep reinforcement learning for co-existing heterogeneous networks control
- Deep learning, deep reinforcement learning for wireless sensor network optimization
- Deep learning, deep reinforcement learning for traffic engineering
- Deep learning, deep reinforcement learning for QoS/QoE management
- Deep learning, deep reinforcement learning for routing in wired and wireless networks
- Deep learning, deep reinforcement learning based applications using wired/wireless network traces
- Deep learning, deep reinforcement learning for IoT and UAV networking
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Published Papers
Sensors - ISSN 1424-8220