Capacity Demand Prediction for Cable Network Devices

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Solution Overview

Problem

Cable system operators face challenges in accurately predicting future capacity demands, leading to unnecessary hardware costs or system inoperability due to inaccurate predictions, particularly in adjusting for individual customer usage.

Innovation Solution

An analysis tool that communicates with electronic devices and networks to monitor capacity and demand parameters, generating a capacity prediction chart that forecasts bandwidth and subscriber trends, allowing operators to determine if future demand will outpace capacity and plan necessary upgrades or migrations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If capacity prediction is made without considering individual customer usage, then prediction process is simple, but prediction accuracy deteriorates

Engineering Contradiction:

Improveprediction process complexityVSAvoidcapacity demand prediction accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent segments capacity prediction into two distinct components: aggregate capacity trends (system-level) and individual customer usage patterns (user-level). By analyzing these segments separately and combining them, the system achieves accurate predictions without requiring complex analysis of every individual customer's behavior in detail.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent creates a universal prediction framework that works for both aggregate system capacity and individual customer capacity. The same basic methodology (comparing historical data to projected demands) applies at multiple levels, making the system versatile and reducing overall complexity while maintaining accuracy.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Reliability

If hardware resources are overestimated, then system operability is ensured, but hardware costs increase

Engineering Contradiction:

Improvesystem operabilityVSAvoidhardware resources

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent performs capacity predictions in advance using historical data and projected growth rates. This preliminary analysis allows operators to plan hardware acquisitions ahead of time, ensuring system operability is maintained while avoiding unnecessary early purchases of hardware resources.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent uses variable growth rate parameters that can be adjusted based on actual system performance and market conditions. By dynamically changing these parameters, the system optimizes hardware resource allocation to match actual demand patterns, preventing both overestimation and underestimation of required resources.

Inventive Principle:

Principle #35Parameter changes

3Quantity of substance

If hardware resources are underestimated, then hardware costs are reduced, but system inoperability occurs

Engineering Contradiction:

Improvehardware resourcesVSAvoidsystem operability

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent incorporates safety margins and threshold alerts in the prediction model. When projected capacity demands approach available resources, the system provides advance warning, allowing operators to acquire additional hardware before system inoperability occurs, thus cushioning against resource underestimation.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

4Measurement precision

If predictions are adjusted for individual customer usage, then prediction accuracy is improved, but data collection complexity increases

Engineering Contradiction:

Improvecapacity demand prediction accuracyVSAvoiddata collection complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary layer that aggregates individual customer usage data into summary statistics before incorporating them into the overall prediction model. This intermediary processing step reduces data collection complexity by working with aggregated metrics rather than raw individual data points, while still capturing the necessary granularity for accurate predictions.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10108905B2Improving an electronic system based on capacity demands of a network device

Publication Date: 2018.10.23 COMCAST CABLE COMM LLC

AI summary

Method of predicting capacity demands on a desired device used to support services for a number of subscribers within a market area having a number of devices. The method includes predicting the capacity demands as a function of historical capacity demands for the desired device and average subscriber capacity demands on the number of devices in the market area.