Server Communication State Detection Using Sub-User Data Changes
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Solution Overview
Problem
Existing change detection systems for network communication between servers rely on fixed rules, leading to false alerts and inability to adapt to diverse user needs, failing to effectively monitor and safeguard network conditions.
Innovation Solution
A computer-implemented system that allows users to input customizable parameters, including metrics, thresholds, and time periods, to detect changes in sub-user data, enabling adaptive monitoring and alerting for network conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed rules are used for change detection, then the system is simple to implement, but it generates false alerts and cannot adapt to diverse user needs
Solution Approach 1:
The patent implements dynamic monitoring rules that automatically adjust thresholds and parameters based on historical data and user behavior patterns. The system transitions from static fixed rules to dynamic adaptive rules that learn and evolve, resolving the contradiction between adaptability and complexity by making the system intelligent rather than merely complex
Solution Approach 2:
The system performs self-learning and self-adjustment by automatically analyzing historical data to establish baseline behaviors and detect anomalies. This self-service capability reduces the need for manual configuration while maintaining high adaptability, effectively managing the complexity-adaptability tradeoff
2Reliability
If fixed rules are applied to all users, then the monitoring system is easy to operate, but it outputs false alerts and fails to satisfy diverse use cases
Solution Approach 1:
The system performs preliminary learning during an onboarding period where it collects historical data and establishes baseline behaviors before正式开始 monitoring. This preliminary action enables the system to achieve high reliability without requiring complex manual configuration, as the adaptive thresholds are automatically learned from actual user patterns
Solution Approach 2:
The system implements feedback loops where alert performance is continuously monitored and used to refine future detection thresholds. User responses to alerts and patterns in false positives feed back into the learning algorithm, automatically improving reliability while maintaining ease of operation through self-optimization
3Adaptability or versatility
If extensive reengineering is performed to modify rules, then the system can satisfy diverse use cases, but it increases development time and complexity
Solution Approach 1:
The patent implements a flexible parameter system where monitoring thresholds, time windows, and detection criteria can be dynamically adjusted without reengineering. Users can modify monitoring parameters through simple configuration interfaces, and the system adapts to diverse use cases by changing parameters rather than requiring structural modifications to the codebase
Data Source
AI summary
Methods and systems for detecting changes in sub-user behavior data for determining a condition of state of communication of a network are disclosed. A method includes prompting a user for user parameters including an object, metric, statistic, threshold information, and a time period. The method further comprises receiving time-series data for the object and metric, and evaluating the user parameters for determining a type of algorithm to apply to the data. The statistic is computed using the applied algorithm. The condition of a state of communication between the servers is computed based on comparing the statistic and the threshold information according to the applied algorithm. The condition of the state of communication of the network is fed back to the user server when the condition is detected.