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Leveraging Deep Learning to Achieve Knowledge-based Autonomous Service Provisioning in Broker-based Multi-Domain SD-EONs with Proactive and Intelligent Predictions of Multi-Domain Traffic
| Content Provider | Semantic Scholar |
|---|---|
| Author | Chen, Xiaoliang Guo, Jiannan Zhu, Zuqing Castro, Alberto Proietti, Roberto Shamsabardeh, M. |
| Copyright Year | 2017 |
| Abstract | This paper demonstrates a knowledge-based autonomous service provisioning framework for multi-domain SD-EONs supported by a broker plane equipped with a deep-learning based traffic estimator. Simulation results show that the proposed framework achieves ∼ 91% traffic prediction accuracy and ∼ 9× blocking reduction compared to conventional solutions. |
| Starting Page | 1 |
| Ending Page | 3 |
| Page Count | 3 |
| File Format | PDF HTM / HTML |
| DOI | 10.1109/ecoc.2017.8346218 |
| Alternate Webpage(s) | http://sierra.ece.ucdavis.edu:29/2017/Xiaoliang_ECOC_MDSDEON_ML.pdf |
| Alternate Webpage(s) | https://doi.org/10.1109/ecoc.2017.8346218 |
| Journal | 2017 European Conference on Optical Communication (ECOC) |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
