A Proactive Restoration Strategy for Optical Cloud Networks Based on Failure Predictions

Failure prediction based on the anomaly detection/forecasting is becoming a reality thanks to the introduction of machine learning techniques. The orchestration layer can leverage on this new feature to proactively reconfigure cloud services that might find themselves traversing an element that is about to fail. As a result, the number of cloud service interruptions can be reduced with beneficial effects in terms of cloud service availability.Based on the above intuition, this paper presents an orchestration strategy for optical cloud networks able to reconfigure vulnerable cloud services (i.e., the ones that would be disrupted if a predicted failure happens) before an actual failure takes place. Simulation results demonstrate that, with a single link failure scenario, proactive restoration can lead to up to 97% less cloud services having to be relocated. This result brings considerable benefits in terms of cloud service availability, especially in low load conditions. It is also shown that these improvements come with almost no increase in the cloud service blocking probability performance, i.e., resource efficiency is not impacted.