Deep reinforcement learning-based optimal deployment of IoT machine learning jobs in fog computing architecture

By increasing the number and variety of areas where IoT technology is being applied, the challenges regarding the design and deployment of IoT applications and services have recently become the subject of many studies. Many IoT applications are machine learning jobs that collect and analyze sensor m...

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Veröffentlicht in:	Computing Jg. 107; H. 1; S. 15
Hauptverfasser:	Bushehrian, Omid, Moazeni, Amir
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Vienna Springer Vienna 01.01.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Cloud computing Computer Appl. in Administrative Data Processing Computer Communication Networks Computer Science Deep learning Edge computing Industrial areas Information Systems Applications (incl.Internet) Internet of Things Machine learning Multilayers Optimization Regular Paper Software Engineering Task scheduling User requirements Fog computing Deep reinforcement learning 90C59 Federated learning IoT application deployment
ISSN:	0010-485X, 1436-5057
Online-Zugang:	Volltext
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