研究目的
To address different issues of planning and control of Flex-Grid/SDM optical networks, including the presentation of the Net2Plan open-source planning tool, a PCE-based Transport-SDN controller, and machine-learning-based QoT classification techniques.
研究成果
The Elastic Networks research network successfully addresses planning and control issues in Flex-Grid/SDM optical networks through the Net2Plan tool, a PCE-based Transport-SDN controller, and machine-learning-based QoT classification techniques, demonstrating high accuracy and efficiency in network planning and control tasks.
研究不足
The study focuses on specific scenarios and technologies (Flex-Grid/SDM networks) and may not cover all possible network configurations or emerging technologies.
1：Experimental Design and Method Selection:
The study uses the Net2Plan open-source planning tool to model Flex-Grid/SDM networks and a PCE-based Transport-SDN controller for packet over flex-grid optical networks. Machine-learning-based QoT classification techniques are also employed.
2：Sample Selection and Data Sources:
The study considers Flex-Grid/SDM networks with MCF-enabled links and various transponders for traffic modelling.
3：List of Experimental Equipment and Materials:
Net2Plan tool, MCF links, transponders with different line rates and modulation formats.
4：Experimental Procedures and Operational Workflow:
The study involves modelling network scenarios, comparing SDM-ROADMs, and applying machine learning for QoT classification.
5：Data Analysis Methods:
The analysis includes performance comparison in terms of throughput and accuracy of QoT classification.
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