Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6888432 | Optical Switching and Networking | 2018 | 23 Pages |
Abstract
The increased data transfers and rapidly evolving cloud services lead to the inevitable need for the new techniques applied to communication networks, such as AI, machine learning, and data analysis. In this paper, we present two approaches that employ the machine learning techniques to enable traffic prediction in Elastic Optical Networks. Results show that the application of adaptive strategies has superior performance, which is a future opportunity for telecommunication operators to improve the efficiency of their network architectures.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Michal Aibin,