Edge-Aided Computing and Transmission Scheduling for LTE-U-Enabled IoT

To facilitate the deployment of private industrial Internet-of-Things (IoT), applying long-term-evolution (LTE) over unlicensed spectrum (LTE-U) is a promising technology, which can deal with the licensed spectrum scarcity problem and the stringent quality-of-service (QoS) requirement via centralize...

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Veröffentlicht in:	IEEE transactions on wireless communications Jg. 19; H. 12; S. 7881 - 7896
Hauptverfasser:	He, Hongli, Shan, Hangguan, Huang, Aiping, Ye, Qiang, Zhuang, Weihua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Computing costs constrained deep reinforcement learning Delays Dynamic scheduling Edge computing Industrial Internet of Things Internet of Things LTE over unlicensed Machine learning Markov processes Mobile edge computing Power consumption Processor scheduling Servers Task analysis task offloading Task scheduling Wireless communication
ISSN:	1536-1276, 1558-2248
Online-Zugang:	Volltext
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