Hash-Based Metadata Synchronization for Multi-Version Metrics
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Solution Overview
Problem
Inconsistencies in metric metadata across different software agent versions lead to inaccurate system analytics, inefficient resource utilization, and increased troubleshooting difficulty due to data redundancy and incorrect standardization, particularly in multi-layered computing systems.
Innovation Solution
A method for synchronizing and aggregating metadata across multiple software agent versions by calculating hash values to label and selectively transmit metadata changes, reducing redundant data transfers and generating self-adapting metrics diagrams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If metadata is transmitted across all software agent versions, then consistency is improved, but network traffic and computing resource waste increase
Solution Approach 1:
The patent extracts only the modified portions of metadata (using delta compression and selective transmission based on hash value changes) rather than transmitting complete metadata sets across all agent versions. This reduces network traffic while maintaining consistency by sending only what is necessary.
Solution Approach 2:
The patent uses hash values as parameters to identify and track metadata changes. By comparing hash values before and after modifications, the system determines what metadata needs synchronization, enabling selective transmission that reduces network overhead while ensuring consistency.
2Measurement precision
If metadata is synchronized across all software agent versions, then data accuracy is improved, but computing resource usage increases
Solution Approach 1:
The patent extracts and processes only the specific metadata elements that have changed (identified through hash value comparison) rather than processing entire metadata sets. This reduces computing resource usage while maintaining metrics accuracy by focusing synchronization efforts only where necessary.
Solution Approach 2:
The patent applies partial synchronization by transmitting only the necessary portion of metadata changes rather than complete metadata sets. This partial action approach maintains accuracy for critical metrics while reducing overall computing resource consumption.
3Loss of information
If complete metadata sets are transmitted, then synchronization completeness is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent extracts only the modified metadata elements using delta compression techniques and selective transmission based on hash value changes. This maintains synchronization completeness by ensuring all necessary changes are transmitted while significantly reducing network bandwidth consumption.
Solution Approach 2:
The patent uses hash value parameters to identify changes and implements selective transmission of only those metadata elements that have modified. This approach maintains complete synchronization for changed elements while reducing overall network bandwidth usage.
4Productivity
If metadata from multiple software versions is aggregated, then comprehensive analytics are improved, but data inconsistency increases
Solution Approach 1:
The patent uses hash value parameters to track and identify metadata changes across different software agent versions. By comparing hash values, the system can aggregate data from multiple versions while maintaining consistency, ensuring that analytics are comprehensive yet reliable.
Solution Approach 2:
The patent implements a feedback mechanism where hash value comparisons provide information about what metadata has changed. This feedback enables the system to aggregate data from multiple software versions while automatically detecting and resolving inconsistencies, maintaining both comprehensiveness and consistency.
Data Source
AI summary
A method, computer system, and a computer program for monitoring synchronization and aggregation are provided. The method may include receiving a plurality of metrics and identifying a plurality of metadata associated with the plurality of metrics. The method may further include calculating a hash value of the plurality of metadata based on the plurality of metrics. The method may further include detecting at least one modification to the plurality of metadata based on the hash value and updating the plurality of metrics based on the at least one modification in which the plurality of metrics are displayed in a self-adapting metric diagram.