Data Characterization Engine for Multicloud Intent Classification

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Information processing systems, especially those in distributed multicloud edge platforms, face challenges in efficiently managing vast amounts of data generated by microservices, as existing methods largely ignore data characterization and rely on applications or storage services, leading to accessibility and cost issues due to nonlocality and untimely reachability assumptions.

Innovation Solution

Implementing a data characterization engine with a machine learning-based classification process that detects data intent, utilizing a multicloud edge platform to automatically select the most appropriate classifier for each application use case, enabling data visibility, access, movement, security, and orchestration decisions through a machine learning classification sub-system, feature extraction and selection sub-system, and parametric meta-learning decisioning sub-system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If data characterization is left to applications or storage services, then application autonomy is maintained, but data management efficiency and accessibility deteriorate

Engineering Contradiction:

Improveapplication autonomyVSAvoiddata management efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent introduces a data characterization engine as an intermediary component between applications and storage services. This engine automatically detects data sources, classifies data by intent, and manages data characterization without requiring applications to perform these tasks themselves, thus maintaining application autonomy while improving data management efficiency

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The data characterization engine operates autonomously to perform data detection, classification, and characterization tasks. It self-manages the complexity of data management by automatically selecting classifiers and determining data intent, freeing applications from these burdens while maintaining system efficiency

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If data is distributed across multiple cloud platforms, then processing capability and scalability are improved, but data accessibility and reachability worsen due to nonlocality

Engineering Contradiction:

Improveprocessing capabilityVSAvoiddata accessibility

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The data characterization engine provides universal data classification capabilities across multiple cloud platforms. By implementing a unified classification system that works consistently across different cloud environments, it enables data accessibility and reachability while maintaining the processing capability and scalability benefits of distributed architecture

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system changes the parameter of data characterization by introducing intent-based classification. This transformation allows data to be identified and accessed based on its purpose and meaning rather than its physical location, improving accessibility across distributed cloud platforms while preserving processing capabilities

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If traditional classification methods are used, then system complexity is reduced, but classification accuracy and data intent detection worsen

Engineering Contradiction:

Improvesystem complexityVSAvoidclassification accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent replaces traditional rule-based or manual classification methods with machine learning-based classification. This substitution enables accurate detection of data intent and automatic selection of appropriate classifiers, significantly improving classification accuracy while the automated nature of the system manages the complexity rather than increasing it

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Speed

If data characterization is not performed, then processing speed is maintained, but data management costs and accessibility issues increase

Engineering Contradiction:

Improveprocessing speedVSAvoiddata management costs

Core Design Contradiction:

SpeedVSLoss of energy

Solution Approach 1:

The data characterization engine performs classification and characterization actions in advance, before data needs to be accessed or processed. By pre-tagging and organizing data based on intent, it enables faster subsequent access and reduces the need for expensive data egress operations, thus maintaining processing speed while reducing management costs

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20240289696A1Data discovery and classification in information processing system environment

Publication Date: 2024.08.29 DELL PROD LP

AI summary

Data characterization techniques in an information processing system environment are disclosed. In one example, at least one processing device is configured to detect a source application associated with data obtained from execution of at least one of a plurality of applications in an information processing system, wherein the plurality of applications comprise services associated with multiple different policies. The processing device is further configured to classify the data to determine an intent associated with the data, wherein classifying comprises utilizing a machine learning classification process.