BGP Configuration Analysis via Statistical Variance
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Solution Overview
Problem
BGP configuration in network systems is challenging due to conflicting policies leading to routing instability, with existing toolkits lacking an accurate method for statistical variance analysis to detect anomalies and ensure policy consistency across distributed configurations.
Innovation Solution
The Infer configuration analysis toolkit employs Statistical Variance Analysis to decompose policies into building blocks (configlets), analyze their existence, completeness, and sequencing, and flag deviant configurations, leveraging business relationship knowledge and external data sources to validate policy consistency and operator intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual or scripting based techniques are used to manage BGP configuration, then flexibility in implementing complex administrative policies is achieved, but configuration accuracy and consistency deteriorate leading to routing instability
Solution Approach 1:
The patent replaces manual/scripting-based BGP configuration management with an automated statistical analysis system that uses variance analysis to detect anomalies and enforce policy consistency across distributed BGP configurations, eliminating human error while maintaining policy flexibility
Solution Approach 2:
The system implements continuous feedback through statistical variance analysis that monitors BGP configurations across the network, automatically identifies deviant configurations, and enables corrective actions to maintain policy consistency and routing stability
2Measurement precision
If statistical variance analysis is implemented to detect configuration anomalies, then configuration accuracy improves, but analysis complexity and computational requirements increase
Solution Approach 1:
The patent transforms the complex problem of BGP configuration analysis by changing parameters to statistical metrics (mean, variance, standard deviation) that simplify the detection of configuration anomalies while maintaining high measurement precision across distributed networks
Solution Approach 2:
The system discards irrelevant configuration variations by establishing baseline statistical norms and only focuses on detecting deviations that exceed acceptable variance thresholds, thereby reducing analysis complexity while maintaining detection accuracy
Data Source
AI summary
Routing and connectivity in the Internet is largely governed by the dynamics and configuration of the Border Gateway Protocol (BGP). A configuration analysis toolkit enables network operators to discover, analyze and diagnose their BGP configuration, policies and peering relationships. Statistical variance analysis in such a toolkit exploits the recurrence of policies in large networks for analysis. In a large network, policies that have similar functions are examined, e.g. all inbound route maps associated with customer autonomous systems. For n occurrences of similar policy P, it is possible to flag k deviant configurations, and evaluate the probability that the deviant configurations are in error. Analysis and policy visualization of implemented BGP configurations enable service providers to move from checking of low-level configuration to extracting analyzable BGP level policy information across a multitude of BGP routers in order to validate consistency of policies and operator intent across distributed BGP configurations using a flexible, customizable analysis engine.