Adaptive edge service deployment in burst load scenarios using deep reinforcement learning

The development of edge computing provides a novel deployment strategy for delay-aware applications, in which applications initially deployed in central servers are shifted closer to end-users for higher-quality and lower-delay services. However, with the growth in the number of end-users and device...

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Veröffentlicht in:	The Journal of supercomputing 2024-03, Vol.80 (4), p.5446-5471
Hauptverfasser:	Xu, Jin, Yu, Huiqun, Fan, Guisheng, Zhang, Jiayin, Li, Zengpeng, Tang, Qifeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Compilers Computer Science Constraint modelling Deep learning Delay Edge computing Interpreters Processor Architectures Programming Languages Quality of service architectures Servers
Online-Zugang:	Volltext
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