A High Reliable Computing Offloading Strategy Using Deep Reinforcement Learning for IoVs in Edge Computing

In view of the serious problems of increasing delay energy consumption and decreasing service quality caused by complex network state and massive computing data in Internet of vehicles (IOT), a high reliable computing offloading strategy based on edge computing is proposed in this paper. Firstly, th...

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Veröffentlicht in:	Journal of grid computing Jg. 19; H. 2
Hauptverfasser:	Wang, Kun, Wang, Xiaofeng, Liu, Xuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.06.2021 Springer Nature B.V
Schlagworte:	Complexity Computation offloading Computer Science Computing costs Edge computing Energy consumption Internet Internet of Vehicles Machine learning Management of Computing and Information Systems Mobile computing Network control Optimization Processor Architectures Quality of service architectures Resource allocation Resource management Software-defined networking Time lag User Interfaces and Human Computer Interaction Vehicles Computing offloading Privacy protection Deep reinforcement learning algorithm Internet of vehicles Software defined network Edge computing
ISSN:	1570-7873, 1572-9184
Online-Zugang:	Volltext
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