Componentized Application Sharing for Image Fidelity and Speed Tradeoffs

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Solution Overview

Problem

Existing application sharing technologies fail to optimally address the varying requirements of image fidelity, speed of delivery, and computing resource consumption across different types of shared applications, often sacrificing either image quality or resource efficiency.

Innovation Solution

A componentized system with pluggable image processing modules that can be configured based on specific application requirements, including image capturing, compression, change detection, and transmission logic, to achieve high fidelity or high-speed transmission depending on the needs of the shared application.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If image fidelity is preserved through lossless capturing and compression, then image quality is improved, but transmission speed and computing resource consumption deteriorate

Engineering Contradiction:

Improveimage fidelityVSAvoidtransmission speed

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The system dynamically adjusts image processing parameters based on application type. For distance learning applications, it uses lossy compression with lower fidelity settings to maximize transmission speed. For medical imaging and architectural design applications, it switches to lossless compression to preserve image fidelity. This dynamic configuration resolves the contradiction by adapting the fidelity-speed tradeoff to specific application requirements.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The invention changes key parameters including compression ratio, image resolution, and update frequency based on application characteristics. For high-speed applications, it reduces compression quality and update rates. For high-fidelity applications, it increases compression quality and maintains higher update rates. This parameter adjustment strategy enables the system to optimize for either fidelity or speed depending on needs.

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If lossless image capturing and compression is used to preserve image detail, then image fidelity is improved, but computing resource consumption increases

Engineering Contradiction:

Improveimage fidelityVSAvoidcomputing resource consumption

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The system applies different image processing qualities to different applications based on their specific requirements. Medical imaging applications receive lossless processing with high computing resources allocated, while distance learning applications receive lossy processing with reduced computing resource allocation. This local quality differentiation resolves the contradiction by concentrating computing resources only where high fidelity is actually needed.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The invention adjusts computing resource allocation parameters dynamically. For applications requiring high fidelity, it allocates more CPU cycles and memory to image processing. For applications where speed is prioritized, it reduces computing resource allocation and uses more efficient but lower-quality compression algorithms. This parameter change strategy enables flexible resource management.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If image update frequency is increased to provide more frequent displays, then information freshness is improved, but network bandwidth consumption and transmission time increase

Engineering Contradiction:

Improveinformation freshnessVSAvoidtransmission time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system dynamically adjusts image update frequency based on application type and network conditions. For real-time collaborative applications, it maintains high update frequencies to ensure information freshness. For asynchronous applications like archived documentation, it uses lower update frequencies. This dynamic adjustment resolves the contradiction by matching update rates to actual information freshness requirements.

Inventive Principle:

Principle #15Dynamics

4Device complexity

If a single application sharing methodology is used for all application types, then system simplicity is maintained, but performance optimization for specific applications deteriorates

Engineering Contradiction:

Improvesystem simplicityVSAvoidperformance optimization

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The invention creates a universal application sharing system that can adapt to multiple application types through configurable parameters. Rather than building separate systems for different applications, it uses a single platform that can be tuned for medical imaging, distance learning, architectural design, or other applications by adjusting compression, resolution, and update frequency settings. This multi-functionality approach maintains system simplicity while enabling performance optimization across diverse applications.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS7835596B2Componentized application sharing

Publication Date: 2010.11.16 WRP IP MANAGEMENT LLC

AI summary

The present invention is a method, system and apparatus for componentized application sharing. The system can include a multiplicity of different pluggable image processing modules. Each of the different pluggable image processing modules can conform to a single interface expected by the application sharing module. Additionally, a communicative coupling can be provided between the application sharing module and a selected one of the different image compression modules.