When Learning Joins Edge: Real-Time Proportional Computation Offloading via Deep Reinforcement Learning

Computation offloading makes sense to the interaction between users and compute-intensive applications. Current researches focused on deciding locally or remotely executing an application, but ignored the specific offloading proportion of application. A full offloading cannot make the best use of cl...

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Vydané v:	2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS) s. 414 - 421
Hlavní autori:	Chen, Ning, Zhang, Sheng, Qian, Zhuzhong, Wu, Jie, Lu, Sanglu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2019
Predmet:	Advanced Deep Q Network Bandwidth Base stations Computation offloading Deep reinforcement learning Delays Energy consumption Expert Buffer Mechanism NP-hard problem Optimization Real-time systems Servers
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