Transformer-Based Network Configuration With Closed-Loop Patch Correction
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Solution Overview
Problem
Conventional network management systems lack closed-loop correction and provenance control, relying on static templates and manual crosswalks, leading to inconsistent service quality and inefficiencies in heterogeneous network environments.
Innovation Solution
A network control function (NCF) using transformer-based models and federated learning to generate schema-constrained configuration patches, applying closed-loop feedback and minimal device-specific updates while maintaining audit support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional static templates and manual crosswalks are used for network management, then device configuration can be applied, but service quality consistency and reliability deteriorate due to lack of closed-loop correction
Solution Approach 1:
The patent implements closed-loop feedback by continuously monitoring network telemetry data and comparing actual service quality against target thresholds. When deviations are detected, the system automatically generates corrective configuration patches and applies them to devices, creating a continuous improvement cycle that ensures service quality consistency without manual intervention
Solution Approach 2:
The system enables network devices to self-configure by automatically generating device-specific configuration patches based on monitored telemetry data and service quality targets. The automated patch generation and application process eliminates manual crosswalks and templates, allowing the system to self-correct and maintain reliability without human intervention
2Reliability
If full device reconfiguration is performed to correct service quality deviations, then service targets can be restored, but network downtime and productivity are reduced
Solution Approach 1:
The patent segments the configuration update process by generating and applying only the specific parameter patches needed to correct service quality deviations, rather than performing full device reconfiguration. This targeted approach restores service targets while minimizing disruption to network operations and maintaining productivity
Solution Approach 2:
The system applies partial configuration updates by generating patches that modify only the bounded subset of parameters causing service quality deviations. This partial action is sufficient to restore service targets without the excessive action of complete device reconfiguration, thereby maintaining network operation continuity
3Measurement precision
If comprehensive network monitoring and analysis are implemented to ensure service quality, then service target compliance improves, but system complexity and energy consumption increase
Solution Approach 1:
The patent implements local quality by monitoring and analyzing only the specific telemetry parameters and device states that are relevant to service quality targets. The system processes data locally at the network control function level, focusing computational resources on critical measurements rather than comprehensive analysis of all network data, thereby reducing energy consumption while maintaining monitoring accuracy
Data Source
AI summary
Systems and methods for configuring and managing a network device with a transformer model under control of a network control function (NCF) are disclosed. A processor of the NCF receives a request that identifies a network management task and associated service targets. The processor forms a token set of schema-defined tokens that represent network context, applies positional encodings to generate an ordered token sequence, and invokes the transformer model to produce a configuration patch. The configuration patch is validated against a schema-constrained decoder that enforces device grammar and is applied to the target network device. Device state and telemetry are read back to obtain a read-back state, which is evaluated against the service targets. When telemetry deviates, the processor generates a further configuration patch that modifies a bounded subset of parameters relative to the read-back state to restore compliance