Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning

In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple logically-isolated slices are constructed on a common roadside network infrastructure. A dynamic RAN slicing fram...

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Veröffentlicht in:	IEEE journal on selected areas in communications Jg. 39; H. 7; S. 2076 - 2089
Hauptverfasser:	Wu, Wen, Chen, Nan, Zhou, Conghao, Li, Mushu, Shen, Xuemin, Zhuang, Weihua, Li, Xu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms constrained reinforcement learning Constraints coupled constraint Delays Dynamic scheduling Heuristic algorithms Internet of Vehicles Machine learning Optimization Quality of service Radio spectra RAN slicing Resource allocation Resource management Roadsides Slicing Task analysis Traffic volume Vehicle dynamics Vehicles vehicular networks Workload workload distribution Workloads
ISSN:	0733-8716, 1558-0008
Online-Zugang:	Volltext
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