Intelligent performance inference: A graph neural network approach to modeling maximum achievable throughput in optical networks
One of the key performance metrics for optical networks is the maximum achievable throughput for a given network. Determining it, however, is a nondeterministic polynomial time (NP) hard optimization problem, often solved via computationally expensive integer linear programming (ILP) formulations. T...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-06-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0137426 |