Fast Adaptive Task Offloading in Edge Computing based on Meta Reinforcement Learning

Multi-access edge computing (MEC) aims to extend cloud service to the network edge to reduce network traffic and service latency. A fundamental problem in MEC is how to efficiently offload heterogeneous tasks of mobile applications from user equipment (UE) to MEC hosts. Recently, many deep reinforce...

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Veröffentlicht in:	arXiv.org 2020-10
Hauptverfasser:	Wang, Jin, Hu, Jia, Min, Geyong, Zomaya, Albert Y, Georgalas, Nektarios
Format:	Artikel
Sprache:	eng
Schlagworte:	Applications programs Cloud computing Communications traffic Computation offloading Computer Science - Distributed, Parallel, and Cluster Computing Computer Science - Learning Edge computing Graph theory Learning Mobile computing Network latency Neural networks Policies Retraining
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