Markov Chain State Predictive Metrics for Application Performance
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Solution Overview
Problem
The analysis of performance reports from user terminals processing various applications is complex due to the large volume of data and variability in user selections and terminal characteristics, making it difficult for operators to decipher and requiring expensive hardware and software resources.
Innovation Solution
A computer program product and method that generates state predictive metrics by identifying operational states, their frequencies, and transitions, using Markov chain modeling and Viterbi algorithms to analyze sequences and predict optimal operational states for improved efficiency, communicated to application servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex hardware and software resources are used to analyze performance reports, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical/computational analysis systems with a mathematical modeling approach using Markov chains. Instead of using expensive hardware and software to process performance reports, the system uses probabilistic state transition models to predict application behavior, substituting physical computing resources with mathematical abstractions that require minimal processing power.
Solution Approach 2:
The patent transforms the analysis approach by changing parameters from direct performance metric analysis to state probability calculations. By defining operational states and transition probabilities rather than analyzing raw performance data directly, the system achieves accurate predictions with simplified processing requirements, resolving the contradiction between precision and complexity.
2Measurement precision
If detailed performance reports are collected from user terminals, then measurement precision is improved, but loss of time increases due to data processing
Solution Approach 1:
The patent applies preliminary action by pre-defining operational states and transition probabilities before actual performance analysis is needed. The Markov chain model is constructed in advance with states representing typical application behaviors and transitions representing state changes. When performance data arrives, the pre-built model immediately processes it through probability calculations rather than requiring complex real-time analysis, significantly reducing processing time while maintaining precision.
3Reliability
If comprehensive performance data is analyzed, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential elements needed for reliable prediction: operational states and transition probabilities. Instead of analyzing all performance data comprehensively, the system extracts key state transitions that characterize application behavior and builds a Markov model based solely on these extracted elements. This selective extraction maintains prediction reliability while eliminating the complexity of processing unnecessary detailed data.
Data Source
AI summary
An application analysis computer obtains reports from user terminals identifying operational states of instances of an application being processed by the user terminals. Sequences of the operational states that the instances of the application have transitioned through while being processed by the user terminals are identified. Common operational states that occur in a plurality of the sequences are identified. For each of the common operational states, a frequency of occurrence of the common operational state is determined. For each state transition between the common operational states in the sequences, a frequency of occurrence of the state transition is determined. State predictive metrics are generated based on the frequencies of occurrence of the common operational states and the frequencies of occurrence of the state transitions. The state predictive metrics are communicated, such as to an application server to control access to the application by user terminals.