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- W2899783011 abstract "This paper proposes the insertion of Deep Learning (DL) Clusters to the Cognitive Packet Network (CPN). Packet routing and traffic management in the CPN are based on the Random Neural Network (RNN) Reinforcement Learning (RL) algorithm. The RNN represents the transmission of information between neurons firing excitatory and inhibitory impulsive spikes; the additional Deep Learning clusters reproduce the technique, the human brain applies when learning, memorizing and taking decisions. This paper proposes the combination of both learning algorithms, RNN and DL as the complete brain model with the addition of a DL cluster structure for Quality of Service parameters; Cybersecurity certificates and finally DL Management clusters for final routing decisions. The presented model has been tested in several simulation settings and network sizes; it has been validated with the CPN itself without DL clusters. The obtained results are encouraging; the presented CPN with DL clusters as a method to transmit, information, learn the environment and take decisions successfully emulates the operation of the human brain." @default.
- W2899783011 created "2018-11-16" @default.
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- W2899783011 date "2018-11-09" @default.
- W2899783011 modified "2023-09-26" @default.
- W2899783011 title "The Cognitive Packet Network with QoS and Cybersecurity Deep Learning Clusters" @default.
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- W2899783011 doi "https://doi.org/10.1007/978-3-030-01054-6_5" @default.
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