Cloud-Edge Collaborative SFC Mapping for Industrial IoT Using Deep Reinforcement Learning

The industrial Internet of Things (IIoT) and 5G have been served as the key elements to support the reliable and efficient operation of Industry 4.0. By integrating burgeoning network function virtualization (NFV) technology with cloud computing and mobile edge computing, an NFV-enabled cloud-edge c...

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Veröffentlicht in:	IEEE transactions on industrial informatics 2022-06, Vol.18 (6), p.4158-4168
Hauptverfasser:	Xu, Siya, Li, Yimin, Guo, Shaoyong, Lei, Chenghao, Liu, Di, Qiu, Xuesong
Format:	Artikel
Sprache:	eng
Schlagworte:	5G mobile communication Algorithms Cloud computing Collaboration Computer architecture Consumption Deep <inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> Q</tex-math> </inline-formula>-learning (DQL) Deep learning Delays Edge computing Industrial applications Industrial Internet of Things industrial Internet of Things (IIoT) Internet of Things Iterative methods Machine learning Mobile computing mobile edge computing (MEC) network function virtualization (NFV) Quality of service Servers Traffic delay
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