AI-Scheduled Certificate Updates to Prevent Network Overload
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Solution Overview
Problem
Existing systems face challenges in efficiently managing bulk certificate updates in large networks, leading to potential system overload, unavailability, and degradation of end-user service experience due to simultaneous certificate renewals or revocations, which can be catastrophic for operators in terms of revenue and user experience.
Innovation Solution
Implementing an AI/ML model at a certificate update orchestrator (CUO) to determine optimized schedules for certificate updates across network functions, staggering updates to avoid simultaneous triggers and coordinating with self-optimizing networks to maintain service continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bulk certificate updates are performed simultaneously across network functions, then certificate security is maintained, but system overload and unavailability occur
Solution Approach 1:
The patent segments the bulk certificate update process by dividing network functions into groups and scheduling updates sequentially across different time slots. The orchestrator assigns update schedules to individual network functions or groups, ensuring that certificate updates are performed in a distributed manner rather than simultaneously, thus preventing system overload while maintaining security requirements.
Solution Approach 2:
The patent implements dynamic scheduling of certificate updates based on real-time system conditions, traffic patterns, and network function priorities. The orchestrator adjusts update timing and pacing dynamically, allowing flexible coordination between security requirements and system availability, preventing catastrophic failures while maintaining updated certificates.
2Productivity
If certificate updates are staggered to avoid system overload, then system availability is maintained, but update complexity increases
Solution Approach 1:
The patent introduces a certificate update orchestrator as an intermediary component that manages the complex scheduling logic. This centralised orchestrator receives update requests, determines optimal schedules considering system conditions and priorities, and coordinates updates across network functions. This intermediary absorbs the complexity of staggered scheduling, presenting a simplified interface to individual network functions while maintaining system availability.
3Productivity
If AI/ML models are used to optimize certificate update schedules, then update efficiency is improved, but computational overhead increases
Solution Approach 1:
The patent applies AI/ML models selectively rather than universally across all network functions. The orchestrator uses machine learning to identify high-priority or critical network functions that benefit most from optimized scheduling, applying computational resources selectively to where they provide maximum efficiency gains while limiting overall computational overhead in the network.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, device, apparatus and computer readable medium for certificate updates. According to embodiments of the present disclosure, a first device receives information of at least one network function. The information at least comprises certificate information of the at least one network function. The first device determines a schedule for triggering certificate update for the at least one network function using an artificial intelligence/machine learning (AI/ML) model on the first device. The first device triggers a certificate update procedure for the at least one network function according to the determined schedule. In this way, it can avoid overload in the system due to bulk certificate updates happening simultaneously.