面向5G雾计算中基于Q-learning的安全中继节点选择方法

doi:10.11959/j.issn.1000-0801.2019176

Abstract

Abstract:

A Q-learning-based optimal dual-relay node selection method was proposed. Firstly, a security fog computing structure model based on social awareness was constructed, and then an optimal dual-relay node selection method based on Q-learning algorithm was designed under this model, which achieved the selection of optimal dual-relay nodes in dynamic environment. Finally, the key generation rate, the selection speed of dual-relay nodes and the selection accuracy of dual-relay nodes in dynamic environment were analyzed. The experimental results show that the scheme can effectively select the optimal dual-relay nodes in dynamic environment, the algorithm converges rapidly to a stable level, and the selection speed of the optimal relay node is effectively improved.

Key words: Q-learning, fog computing, 5G network, social awareness, physical layer security

CLC Number:

TP393

Shanshan TU,Jinliang YU,Yuan MENG,M WWAQAS,Lei LIU. Secure relay node selection method based on Q-learning for fog computing in 5G network[J]. Telecommunications Science, 2019, 35(7): 60-68.

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References 21

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