Multi-Modal Data Distribution for Subscription Rounding Variance

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Solution Overview

Problem

Digital commerce systems experience discrepancies between initial and recurring transaction conditions, leading to issues like computer processing delays, data storage shortages, and communication network congestion due to automated resolution of price rounding errors in subscription models.

Innovation Solution

Implement multi-modal data distribution logic to normalize variance in subscription models using variance distribution modes such as front loading, mid loading, tail loading, and uniform loading to maintain zero variance across billing periods.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If automated resolution of transaction condition discrepancies is implemented, then transaction accuracy is improved, but system resource strain (processing delays, storage shortages, network congestion) worsens

Engineering Contradiction:

Improvetransaction accuracyVSAvoidsystem resource capacity

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent segments the resolution of transaction condition discrepancies by implementing multiple variance distribution modes (pro-rata, equal, priority-based) that can be selected based on system conditions. This segmentation allows the system to handle different types of discrepancies using different strategies, reducing overall system strain while maintaining accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the parameter of variance distribution by introducing multiple distribution modes that can be dynamically selected. By adjusting the distribution parameter based on system capacity and transaction characteristics, the system resolves discrepancies accurately without consistently straining resources.

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If multiple variance distribution modes are implemented, then adaptability to different transaction scenarios is improved, but system complexity worsens

Engineering Contradiction:

Improvevariance distribution flexibilityVSAvoiddata management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements dynamic variance distribution by allowing the system to select different distribution modes based on real-time conditions. The system can switch between pro-rata, equal, and priority-based distribution approaches, making the data management adaptable without requiring complex manual configuration for each scenario.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent creates a universal variance distribution framework that handles multiple transaction scenarios through a single set of distribution modes. This multi-functional approach allows the same system structure to adapt to different transaction types, reducing overall complexity while maintaining versatility.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250328887A1Multi-modal data distribution in an information processing system

Publication Date: 2025.10.23 DELL PROD LP

AI summary

Data management techniques for multi-modal data distribution in information processing systems are disclosed. For example, a method computes, at a first processing node of an information processing system in accordance with a subscription model managed by the first processing node, a variance in an attribute of the subscription model with respect to a second processing node of the information processing system. The method receives, at the first processing node from the second processing node, a selection of a variance distribution mode from a plurality of variance distribution modes. The method applies, at the first processing node, the selected variance distribution mode to the attribute of the subscription model.