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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Vydané v:	IEEE transactions on wireless communications Ročník 19; číslo 12; s. 7881 - 7896
Hlavní autori:	He, Hongli, Shan, Hangguan, Huang, Aiping, Ye, Qiang, Zhuang, Weihua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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