Symbolic Query System for Network State Analysis
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Solution Overview
Problem
Existing systems face inefficiencies in monitoring and analyzing complex network systems due to the need for explicit enumeration of all elements, which is computationally costly and not scalable for large systems with fast-changing states.
Innovation Solution
The method employs symbolic representations and Boolean functions to formulate queries that operate on sets of system elements, constructing a symbolic graph to efficiently determine system states, available resources, malfunctions, or alerts, using techniques like ROBDD, SAT, or SMT solvers, allowing for efficient computation on entire sets rather than individual elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If explicit enumeration of all system elements is used for monitoring and analysis, then complete system state information can be obtained, but computational cost increases and scalability deteriorates for large systems
Solution Approach 1:
The patent uses symbolic representations (copies) of system elements instead of explicit enumerations. Each system element type is represented by a symbolic variable that can represent multiple concrete elements simultaneously. This allows the system to work with compact symbolic models rather than exhaustive lists of individual elements, dramatically reducing computational cost while preserving the ability to analyze complete system states through symbolic manipulation and model checking techniques
Solution Approach 2:
The patent transforms the representation parameters from concrete element identifiers to symbolic variables. By changing the parameter space from individual element indices to symbolic representations with associated constraints, the system can efficiently query and analyze system states without explicitly enumerating all elements. This parameter transformation enables scalable analysis of large systems through symbolic model checking rather than brute-force enumeration
2Measurement precision
If explicit enumeration of all system elements is used for monitoring and analysis, then accurate system state determination can be achieved, but computational cost increases for large-scale systems
Solution Approach 1:
The patent creates symbolic copies that represent sets of system elements. Instead of processing each element individually, the symbolic representation allows simultaneous manipulation of entire classes of elements. This copying approach maintains analytical accuracy by preserving the structural relationships and constraints that define system state, while dramatically reducing the computational resources needed compared to explicit enumeration of all elements
Solution Approach 2:
The symbolic variables and representations serve multiple functions simultaneously: they represent individual elements, sets of elements, and system states; they encode constraints and relationships; and they enable various types of queries and analyses. This multi-functionality eliminates the need for separate data structures and algorithms for different analysis tasks, reducing overall system complexity while maintaining accurate system state determination
3Measurement precision
If standard algorithms that explicitly enumerate all system elements are used, then detailed element-level analysis is possible, but the system cannot respond instantaneously to fast-changing states
Solution Approach 1:
The patent uses symbolic copies that can be manipulated and queried in constant or logarithmic time regardless of the number of concrete elements they represent. When system states change, the symbolic representations can be updated and re-evaluated instantly through efficient symbolic computation and model checking algorithms, providing instantaneous response to changes while maintaining the ability to perform detailed element-level analysis when needed
Solution Approach 2:
The patent performs preliminary symbolic analysis to pre-compute and cache system properties, constraints, and relationships. By preparing symbolic models and constraint systems in advance, the system can rapidly respond to state changes by reusing pre-computed information and performing incremental updates rather than re-analyzing all elements from scratch, enabling instantaneous response while maintaining detailed analysis capabilities
Data Source
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AI summary
Provided is a method for analyzing a state of a system. The method comprises formulating a symbolic query using Boolean functions that describe relations between system elements, generating or updating a symbolic representation for each relation, and performing the symbolic query based on the generated or updated symbolic representation.