Data Flow Aggregation Period Variation for Metadata Granularity

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Solution Overview

Problem

Current data mining techniques face challenges in efficiently identifying valuable metadata from network traffic, as low-value and high-value flows consume equal processing resources and storage, making it difficult to differentiate and prioritize resource allocation based on the value of network traffic patterns.

Innovation Solution

The method involves varying the aggregation periods for data flows based on their value, where high-value flows are aggregated into database records with shorter intervals and low-value flows with longer intervals, allowing for greater granularity and visibility of valuable metadata, thereby optimizing resource allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If equal aggregation periods are used for all data flows, then processing and storage are simplified, but resource allocation cannot be optimized based on data value

Engineering Contradiction:
Improveprocessing simplicityVSAvoidresource allocation efficiency
Core Design Contradiction:
Ease of manufactureVSProductivity

Solution Approach 1:

The patent applies local quality by assigning different aggregation periods to different data flows based on their assigned values. High-value flows receive shorter aggregation periods for detailed analysis, while low-value flows receive longer aggregation periods for resource efficiency. This differentiated approach optimizes resource allocation while maintaining processing feasibility.

Inventive Principle:
Principle #3Local quality

2Measurement precision

If shorter aggregation periods are used for high-value flows, then metadata visibility and granularity are improved, but processing and storage complexity increases

Engineering Contradiction:
Improvemetadata granularityVSAvoidprocessing complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent changes the aggregation period parameter dynamically based on the assigned value of each data flow. By adjusting this temporal parameter, the system achieves different levels of metadata granularity for different flows, allowing precise analysis of high-value flows while maintaining manageable processing complexity through automated value-based classification.

Inventive Principle:
Principle #35Parameter changes

3Loss of energy

If longer aggregation periods are used for low-value flows, then resource consumption is reduced, but potential valuable patterns may be lost

Engineering Contradiction:
Improveprocessing resource consumptionVSAvoidpattern detection accuracy
Core Design Contradiction:
Loss of energyVSLoss of information

Solution Approach 1:

The patent applies local quality by assigning different aggregation periods to different data flows based on their assigned values. High-value flows receive shorter aggregation periods for detailed analysis, while low-value flows receive longer aggregation periods for resource efficiency. This differentiated approach optimizes resource allocation while maintaining processing feasibility.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The system performs preliminary action by assigning values to data flows before aggregation. This pre-classification allows the system to determine appropriate aggregation periods in advance, ensuring that even low-value flows are processed with sufficient detail to detect meaningful patterns while avoiding unnecessary processing of truly insignificant data.

Inventive Principle:
Principle #10Preliminary action

4Loss of information

If all flows are processed with high granularity, then comprehensive metadata is captured, but storage and processing resources are wasted on low-value data

Engineering Contradiction:
Improvemetadata completenessVSAvoidstorage resource usage
Core Design Contradiction:
Loss of informationVSQuantity of substance

Solution Approach 1:

The patent applies local quality by assigning different aggregation periods to different data flows based on their assigned values. High-value flows receive shorter aggregation periods for detailed analysis, while low-value flows receive longer aggregation periods for resource efficiency. This differentiated approach optimizes resource allocation while maintaining processing feasibility.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The patent changes the aggregation period parameter dynamically based on the assigned value of each data flow. By adjusting this temporal parameter, the system achieves different levels of metadata granularity for different flows, allowing precise analysis of high-value flows while maintaining manageable processing complexity.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentUS10999167B2Varying data flow aggregation period relative to data value
Publication Date: 2021.05.04 AT&T INTELLECTUAL PROPERTY I L P
  • US10999167B2 patent drawing
  • US10999167B2 patent drawing
  • US10999167B2 patent drawing

AI summary

In one example, the present disclosure describes a device, computer-readable medium, and method for varying the aggregation periods for data flows relative to the values of the data contained in the flows. For instance, in one example, a method includes intercepting a first flow and a second flow traversing a communications network, assigning a first value to the first flow and a second value to the second flow, wherein the first value is higher than the second value, aggregating the first flow into a first database record according to a first aggregation period, aggregating the second flow into a second database record according to a second aggregation period that is longer than the first aggregation period, and storing the first database record and the second database record in a database.