Abstract

The Quasi-OPtimal SoftwarE Recommendation Analytics system (OPERA) is configured to scan a customer network on a 24/7 basis. OPERA is also configured to proactively notify the customer if a software upgrade is necessary, as well as notify the customer which device or group of devices should be upgraded to the exact needed software versions. The software recommendations are tailored on a per-customer basis and have improved accuracy by using reinforcement learning, constrained based optimization, and an Integer Linear Programming model. OPERA may also presents customers with a composite risk score for the current network and recommend upgrades which will minimize the risk.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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