Probabilistic Data Combiner for DSL Network Characterization

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Solution Overview

Problem

Existing DSL systems face challenges in reliably combining data from multiple sources to characterize and diagnose communication networks, leading to unreliable analysis results due to simplistic models that ignore uncertainty factors and lack confidence levels.

Innovation Solution

A data collector combiner system that probabilistically combines data from multiple sources using Bayes' theorem to estimate DSL characterizing parameters, accounting for uncertainty factors such as measurement errors and deviations from ideal models.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If data from multiple sources is combined using simplistic models, then the analysis process is simplified, but the reliability of the results deteriorates due to ignoring uncertainty factors

Engineering Contradiction:

Improvecomplexity of data combination processVSAvoidreliability of analysis results

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent transforms the data combination process by changing the mathematical parameters and models used. Instead of simplistic deterministic models, it employs probabilistic models that incorporate uncertainty parameters such as measurement errors and confidence intervals. This allows the system to maintain manageable complexity while significantly improving result reliability through statistical rigor.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent introduces probabilistic reasoning and statistical models as intermediary layers between raw data from multiple sources and final analysis results. These intermediaries process the data by accounting for uncertainty factors, measurement errors, and confidence levels, thereby bridging the gap between simple data aggregation and reliable conclusion drawing without requiring direct complex integration of all source variations.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If probabilistic reasoning is used to combine data from multiple sources, then the accuracy of parameter estimation is improved, but the computational complexity increases

Engineering Contradiction:

Improveaccuracy of DSL parameter estimationVSAvoidcomputational complexity of data combination

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies partial probabilistic reasoning selectively to the most critical parameters and data sources rather than uniformly to all data. By identifying which parameters require highest precision and which data sources contribute most significantly to uncertainty, the system applies complex probabilistic models only where necessary, achieving high accuracy for key parameters while limiting overall computational complexity through targeted application of sophisticated methods.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS8902958B2Methods and apparatus to combine data from multiple source to characterize communication systems

Publication Date: 2014.12.02 AT&T INTELLECTUAL PROPERTY I L P

AI summary

A data collector combiner, a network management system, a DSL Optimizer (DSLO), or any combination thereof collects data, parameter(s), characteristic(s), information, or any combination thereof from two or more data sources. The data collector probabilistically combines at least the first and second data to estimate at least one DSL characterizing parameter.