Service Asset Association via Alias Term Scoring

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Solution Overview

Problem

Distributed computing systems face complexity in managing services across multiple assets, making it difficult to track influences and respond to events efficiently, such as maintenance, error handling, and identifying associated server devices.

Innovation Solution

A computerized method that collects metadata from computing assets, identifies alias terms associated with services, generates service association scores using a term-score mapping, and identifies a subset of assets with scores exceeding a threshold to determine service associations, enabling automated and accurate identification of service-related assets.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If distributed computing systems use a wide variety of different computing assets to provide increased flexibility and power, then the system's functional capability and versatility are improved, but the complexity of managing such systems increases substantially

Engineering Contradiction:

Improvefunctional capabilityVSAvoidsystem management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary system that automatically discovers and maps relationships between services and computing assets. This intermediary mechanism analyzes metadata, identifies alias terms, and generates service association scores to automatically track which assets are related to which services, thereby reducing the manual management complexity that arises from using diverse computing assets

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system changes the parameter of asset identification from manual tracking to automated scoring based on metadata analysis. By generating service association scores that indicate the likelihood of asset-service relationships, the system transforms the management approach from complex manual tracking to automated parameter-based identification

Inventive Principle:

Principle #35Parameter changes

2Productivity

If services are distributed across many different server devices, then system flexibility and processing power are improved, but tracking the influences and effects of services across assets becomes increasingly difficult

Engineering Contradiction:

Improveprocessing powerVSAvoidservice influence tracking

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent replaces manual tracking mechanisms with automated computational analysis. The system uses processors to automatically collect metadata, identify alias terms, generate service association scores, and determine asset-service relationships, substituting mechanical manual tracking with automated electronic detection and measurement processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the computing assets themselves to provide metadata that automatically reveals their relationships to services. The assets' own metadata and alias terms are used by the system to self-identify their associations without requiring external manual tracking

Inventive Principle:

Principle #25Self-service

3Measurement precision

If manual analysis is used to identify service-associated computing assets, then accuracy can be maintained, but efficiency in maintenance, error response, and cleanup processes is reduced

Engineering Contradiction:

Improveidentification accuracyVSAvoidresponse efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system uses feedback loops where service association scores are generated based on metadata analysis, these scores are evaluated against thresholds to identify associated assets, and the results can be used to refine future analysis. This feedback mechanism maintains accuracy while enabling automated high-speed processing that improves response efficiency

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs partial analysis by generating service association scores for all assets and then applying threshold filtering to identify the relevant subset. This approach of performing excessive analysis on all assets and then filtering maintains accuracy while enabling automated processing that improves overall efficiency

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11687598B2Determining associations between services and computing assets based on alias term identification

Publication Date: 2023.06.27 MASTERCARD INT INC

AI summary

The disclosure herein describes determining computing assets associated with a service. Metadata from one or more computing assets of a computing system is collected. One or more alias terms are identified in the collected metadata of the one or more computing assets, wherein the alias terms are associated with the service. Service association scores are generated for the one or more computing assets based on the identified one or more alias terms and a term-score mapping. Each service association score indicates a likelihood that a computing asset is used for a service. A subset of computing assets of the one or more computing assets is identified. The subset of computing assets includes computing assets with service association scores that exceed a service association threshold. Computing assets of the service are identified based on the identified subset, thereby reducing the need for manual identification of asset-service associations.