Higher-Order Logic Expert Systems for Network Alarm Correlation
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Solution Overview
Problem
Current expert systems for analyzing network behavior are limited by their reliance on first-order logic, which is cumbersome, monolithic, and lacks the flexibility to effectively model complex network topologies and behaviors, leading to inefficiencies in alarm correlation and remediation across diverse network elements.
Innovation Solution
The use of second- and higher-order logic to analyze event descriptive information, enabling the creation of lower-logic modules that can determine events, causal events, and remedial actions, thereby providing a more abstract and flexible framework for generating customized expert systems that can adapt to specific network configurations and topologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If first-order logic is used to implement expert systems, then the systems can be implemented with current technology, but the systems become monolithic, cumbersome, and lack flexibility to effectively parameterize and encode unifying abstractions across diverse network elements
Solution Approach 1:
The patent segments the monolithic first-order logic system into hierarchical levels: first-order logic for specific instances and second-order logic for general abstractions and unifying concepts. This segmentation allows the system to maintain both specificity and generality without becoming monolithic, enabling flexible parameterization across diverse network elements while avoiding the verbosity and rigidity of pure first-order logic implementations.
2Adaptability or versatility
If second-order and higher-order logic are used to implement expert systems, then the systems gain flexibility and ability to express unifying abstractions, but the implementation complexity increases
Solution Approach 1:
The patent introduces an intermediary translation layer that converts second-order and higher-order logic specifications into executable first-order logic code. This intermediary mechanism allows the system to leverage the expressive power of higher-order logic for defining abstractions and customized expert systems, while the translation layer handles the implementation complexity by generating standard first-order logic that can be executed by existing systems, thus resolving the contradiction between expressiveness and implementability.
3Ease of manufacture
If first-order logic expressions are used, then the expert systems can be implemented with current technology, but the syntactic limitations make the logic cumbersome and difficult to maintain
Solution Approach 1:
The patent adds a second-order dimension to the logic system, allowing expressions to operate at multiple levels: first-order for specific network element instances and second-order for general patterns and abstractions. This dimensional enhancement enables more intuitive and maintainable expressions by capturing unifying concepts at the second-order level, which automatically apply to multiple first-order instances, thereby reducing the verbosity and maintenance burden of first-order logic while remaining implementable through translation mechanisms.
Data Source
AI summary
The present invention is directed to a system and method for applying second- and higher-order logic to analysis of event descriptive information, such as alarms, error messages, and fault signals.