Deep Learning for Multi-Step Performance Prediction in Operational Optical Networks

2020 ◽  
Author(s):  
Ameni Mezni ◽  
Douglas W. Charlton ◽  
Christine Tremblay ◽  
Christian Desrosiers
Keyword(s):  
Deep Learning ◽  
Optical Networks ◽  
Performance Prediction

scholarly journals Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability

2017 ◽  
Vol 9 (6) ◽  
pp. 899 ◽  
Author(s):  
Joonhyuck Lee ◽  
Dongsik Jang ◽  
Sangsung Park
Keyword(s):  
Deep Learning ◽  
Prediction Model ◽  
Performance Prediction ◽  
Corporate Performance ◽  
Technical Capability

A Deep Learning Based RSA Strategy for Elastic Optical Networks

2019 ◽  
Author(s):  
Jiaoliang Yu ◽  
Bokai Cheng ◽  
Cheng Hang ◽  
Yunfei Hu ◽  
Shixin Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optical Networks

System Performance Prediction With the Gaussian Noise Model in 100G PDM-QPSK Coherent Optical Networks

2013 ◽  
Vol 31 (21) ◽  
pp. 3352-3360 ◽  
Author(s):  
Andrew J. Stark ◽  
Yu-Ting Hsueh ◽  
Thomas F. Detwiler ◽  
Mark M. Filer ◽  
Sorin Tibuleac ◽  
...  
Keyword(s):  
Optical Networks ◽  
Performance Prediction ◽  
Gaussian Noise ◽  
System Performance ◽  
Noise Model

scholarly journals Dynamic access control and security performance prediction for IoT networking using a novel deep learning technique

2021 ◽  
Author(s):  
Sriramya P. ◽  
A.K. Reshmy ◽  
R. Subhashini ◽  
Korakod Tongkachok ◽  
Ajay Prakash Pasupulla ◽  
...  
Keyword(s):  
Deep Learning ◽  
Access Control ◽  
Real Time ◽  
Performance Prediction ◽  
Dynamic Models ◽  
Security Risk ◽  
Time Data ◽  
Iot Security ◽  
Area Of Interest ◽  
Dynamic Access Control

Abstract Internet of things (IoT) has increased an importance for an area of interest in many devices. Then, the applications such as sensitive home sensors, medical devices, wireless sensors,and other devices are related to IoT network. The transmission of big data is subject to a possible attack that could cause network interruptions and problems with security. The security performance prediction is important for IoT networks to address complicated security issues in real-time which one of the attacks can freely threaten its global performance. Initially,investigate the safety performance of security intelligent prediction techniques is linking with deep learning algorithms into the IoT security risks. This contribution provides a CNN model that improves IoT security risk assessment (SRA) performance. Then, the access control techniques are changed with IoT-like dynamic systems with the number of items spread all over the place. Therefore, dynamic access control models are necessary. Thesedesign not individual use strategies of access but incorporate environmental and real-time data to predict the decision on access. The risk-based access control approach is one of those dynamic models. To decide the access decision, this model assesses the security risk value associated with the access request. This assessment of the model proposed results from the performance and accuracy of IoT networks.

Potential failure cause identification for optical networks using deep learning with attention mechanism

2021 ◽  
Author(s):  
Chunyu Zhang ◽  
Danshi Wang ◽  
Jinwei Jia ◽  
Lingling Wang ◽  
Kun Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optical Networks ◽  
Attention Mechanism ◽  
Potential Failure

Pulse shaping using diffractive optical networks designed by deep learning

2021 ◽  
Author(s):  
Muhammed Veli ◽  
Deniz Mengu ◽  
Nezih T. Yardimci ◽  
Yi Luo ◽  
Jingxi Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optical Networks ◽  
Pulse Shaping
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