Abstract
[0001] The present disclosure relates to systems and methods for a temporal prediction model for executing orchestration functions in optical networks. Predictive modeling for provisioning optical services and functions within an optical communication network involves a trained temporal prediction model (“model”). This begins with collecting execution times from each device and interface for various orchestration functions, followed by timing processes at each network element (NE), including issuing, acknowledging, executing commands, and waiting for devices to reach a ready state. The model then establishes correlations between different functions and their provisioning times based on network complexity. Temporal dependencies are recorded between issuing orchestration commands and achieving stable monitoring states. Using these insights, a predictive model is constructed at the domain controller level, accounting for process correlations and dependencies to improve provisioning accuracy. Advantageously, the model enables prediction of execution functions unique to each network.
Creative Commons License
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Recommended Citation
Anonymous, "Temporal Prediction Model for Executing Orchestration Functions in Optical Network", Technical Disclosure Commons, (November 03, 2025)
https://www.tdcommons.org/dpubs_series/8831