Distributed System Resource Interaction Modeling
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Solution Overview
Problem
Large distributed systems are complex and challenging to understand due to the numerous interconnected resources, making it difficult to ascertain the effects of one resource on others, necessitating a modeling system that facilitates understanding interactions between resources.
Innovation Solution
A modeling system that includes a data processing device and non-transitory memory, which monitors interactions, detects state changes, identifies causing entities, and updates a model to indicate relationships between resources, allowing for the determination of impacts and providing alternative resources to mitigate effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the size of a distributed system increases to include more interconnected resources, then the system's functionality and capability are improved, but the complexity and difficulty of understanding resource interactions increase
Solution Approach 1:
The patent segments the complex distributed system into individual monitorable resources and their interactions. Each resource is monitored independently for state changes, and relationships are established between specific resources rather than attempting to model the entire system as a monolithic complex structure. This segmentation allows the system to scale while maintaining understandability through localized monitoring and relationship tracking.
2Measurement precision
If comprehensive monitoring of all resource interactions is implemented, then the accuracy of understanding system relationships is improved, but the computational overhead and system resource consumption increase
Solution Approach 1:
The patent implements partial monitoring by focusing only on detecting state changes in resources rather than continuously monitoring all aspects of resource behavior. The system monitors for changes and only establishes relationships when state changes occur within a threshold time period, rather than comprehensively analyzing all resource interactions. This approach achieves sufficient relationship detection accuracy while reducing computational overhead by avoiding excessive monitoring of unchanged resources.
3Speed
If the monitoring threshold time period is reduced to detect relationships more quickly, then the responsiveness of relationship detection is improved, but the risk of false positives and inaccurate relationship identification increases
Solution Approach 1:
The patent uses a threshold time period parameter that can be adjusted to balance detection speed and accuracy. By setting an appropriate threshold, the system responds quickly enough to capture meaningful relationships while filtering out spurious correlations that would occur with overly aggressive timing. The threshold acts as a configurable parameter that allows optimization based on specific system characteristics and requirements.
Data Source
AI summary
A modeling system including a data processing device in communication with a non-transitory memory storing a model modeling interactions of resources of a distributed system. The data processing device executes instructions that cause the data processing device to implement a system monitor that monitors interactions of the resources of the distributed system and builds the model. The system monitor detects a state change of a first resource of the distributed system and identifies an entity causing the state change of the first resource. The system monitor determines whether a second resource of the distributed system changes state within a threshold period of time after the first resource changed state. The system monitor updates the model to indicate a relationship between the first resource, the second resource and the identified entity, in response to the first resource and the second resource changing state within the threshold time period.