Self-optimized network: When Machine Learning Meets Optimization-Reference-Cited by-同舟云学术

Self-optimized network: When Machine Learning Meets Optimization

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Global Communications Conference (GLOBECOM)
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Author:

Nacef Abdelhakim¹,Bagaa Miloud²,Aklouf Youcef¹,Kaci Abdellah³,Dutra Diego Leonel Cadette⁴,Ksentini Adlen⁵

Affiliation:

1. University of Sciences and Technology Houari Boumediene (USTHB),Research laboratory in Informatics, Intelligence, Mathematics and Applications (RIIMA),Algeria

2. CSC,Finland

3. Ecole Nationale Supérieure de Technologie (ENST),Laboratoire des Technologies Innovantes (LTI),Algeria

4. Federal University of Rio de Janeiro,Rio de Janeiro,Brazil

5. EURECOM,Sophia-Antipolis,France,06410

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9685019/9685006/09685681.pdf?arnumber=9685681

Reference18 articles.

1. A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges

2. SDN-based hybrid server and link load balancing in multipath distributed storage systems

3. Scalable orchestration of software defined service overlay network for multipath transmission

4. On SDN-Driven Network Optimization and QoS Aware Routing Using Multiple Paths

5. Safeguard Network Slicing in 5G: A Learning Augmented Optimization Approach

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