Digital Fingerprinting for Redundant Content Transfer Management
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Solution Overview
Problem
Existing methods for identifying and managing digital content transfers over networks are inefficient in detecting redundant content, leading to unnecessary resource consumption and cost, as they fail to account for variations in format, resolution, and filename changes.
Innovation Solution
The use of digital fingerprinting to create a unique identifier for digital content, allowing for comparison and identification of similar or identical content across variations, thereby preventing redundant downloads by checking local storage on user devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If digital content is transferred over the network without redundancy detection, then users can access content quickly, but bandwidth and storage resources are wasted due to redundant downloads
Solution Approach 1:
The system performs preliminary actions by calculating digital fingerprints of content before transfer and storing them in advance. When a user requests content, the system proactively checks the fingerprint against the database before initiating download, preventing redundant transfers before they occur. This preliminary detection mechanism resolves the contradiction by avoiding wasted bandwidth while maintaining quick access for legitimate new content.
Solution Approach 2:
The patent introduces a fingerprint database as an intermediary between the content source and user devices. This intermediary stores digital fingerprints and provides quick comparison capability, enabling the system to identify redundant content without transferring actual files. The intermediary resolves the contradiction by enabling rapid redundancy detection that prevents unnecessary bandwidth consumption while maintaining efficient content delivery.
2Loss of energy
If digital fingerprinting is implemented to detect redundant content, then bandwidth and storage are conserved, but system complexity increases due to fingerprint calculation and database management
Solution Approach 1:
The system extracts only the essential identifying feature (digital fingerprint) from the complete content, separating this lightweight identifier from the actual content files. By taking out just the fingerprint for storage and comparison purposes, the system achieves redundancy detection with minimal complexity overhead. This extraction principle resolves the contradiction by enabling storage conservation through simple fingerprint databases rather than complex content analysis systems.
Solution Approach 2:
The patent transforms the content identification problem from comparing entire files to comparing condensed fingerprint parameters. By changing the parameter being compared from full content data to compact fingerprint representations, the system reduces computational complexity and database requirements while maintaining effective redundancy detection. This parameter transformation resolves the contradiction between storage conservation and system complexity.
3Loss of energy
If content is transferred without checking local storage, then network traffic increases, but simple transfer protocols are maintained
Solution Approach 1:
The system creates and uses copies of content identifiers (fingerprints) rather than copying actual content files for comparison purposes. This copying approach allows the protocol to check for redundancy by comparing lightweight fingerprint data instead of transferring or comparing full content files. This resolves the contradiction by reducing network traffic through fingerprint-based verification while keeping the protocol simple and efficient.
Data Source
AI summary
A computer system receives digital content for communication to a user. Digital fingerprints are calculated from the digital content. The fingerprints are compared to identify redundant digital content. Digital identifications associated with the digital fingerprints are communicated to a user device to determine whether the digital content exists in local storage.