Ciena Corporation

Shady A Mohammed

David Côté

Shervin Shirmohammadi

Thomas Triplet

Emil Janulewicz

Shelley A Bhalla

Sa'di Altamimi

Ayse Rumeysa Mohammed

Basel Altamimi

Systems, methods, and computer-readable media are provided for recommending actions to be taken in a network for optimizing or improving the operability of the network. A method, according to one implementation, includes a first step of receiving raw, unprocessed data that is obtained directly from one or more network elements of a network. The method includes second step of determining one or more remedial actions using a direct association between the raw, unprocessed data and the one or more remedial actions.

Action recommendation engine (ARE) for network operations center (NOC) solely from raw un-labeled data

Systems and methods for recommending actions in a closed-loop system are provided. In one embodiment, an Action Recommendation Engine (ARE) may include a processor and memory configured to store computer programs having instructions that cause the processor to obtain input data pertaining to a state of a network and obtain information regarding one or more historical actions performed on the network. Also, the instructions may cause the processor to utilize a Machine Learning (ML) model for imposing one or more current actions on the network, the one or more current actions selected from the group of procedures consisting of: a) suggesting one or more remediation actions that, when performed, transition the network from a problematic state to a normal state, and b) identifying one or more root causes in response to detecting a transition in the network from a normal state to a problematic state.

Action recommendation engine (ARE) of a closed-loop machine learning (ML) system for controlling a network

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Nepean, Canada

Shady A Mohammed