Data Confidence Fabric With TSN for Deterministic Trusted Delivery
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Solution Overview
Problem
Existing computing systems lack the ability to reliably deliver data with high confidence levels, particularly in time-sensitive applications, due to uncertainties in data quality and delivery timing.
Innovation Solution
Implementing a data confidence fabric (DCF) network with time sensitive networking (TSN) to ensure deterministic data delivery and incorporate confidence scores based on trust insertion technologies, including hardware and software annotations, to enhance data trustworthiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is transmitted over standard networking infrastructure, then data delivery speed may be improved, but data delivery reliability and timing确定性 deteriorate
Solution Approach 1:
The patent segments data transmission into different priority classes using TSN protocols, separating time-sensitive data from regular data traffic. This segmentation allows critical data to receive dedicated network resources and deterministic timing guarantees while maintaining high overall network throughput and speed.
Solution Approach 2:
The patent implements counterbalancing mechanisms where TSN synchronization protocols and confidence scoring systems compensate for inherent network uncertainties. These mechanisms actively counteract timing variations and reliability issues in standard networking infrastructure through predetermined synchronization and verification procedures.
2Reliability
If confidence scoring mechanisms are implemented, then data trustworthiness is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal confidence scoring framework that works across multiple data types, transmission paths, and application scenarios. This multi-functional system uses standardized metrics and protocols that can be applied universally throughout the network, reducing the need for application-specific complexity while maintaining comprehensive data trustworthiness assessment.
Solution Approach 2:
The patent performs confidence scoring and trust verification in advance before data is fully processed or acted upon. By pre-establishing confidence metrics, validating data provenance upfront, and performing preliminary trust assessments, the system avoids complex real-time verification while ensuring data reliability when needed.
3Loss of time
If time sensitive networking is implemented, then data delivery timing is improved, but network configuration complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where network devices automatically synchronize their clocks and adjust their timing based on TSN protocols without requiring manual configuration. The system performs autonomous timing calibration, automatic path selection, and dynamic resource allocation, reducing configuration complexity while maintaining precise data delivery timing.
Solution Approach 2:
The patent employs feedback loops where network devices continuously monitor timing performance and automatically adjust their operations based on measured deviations. Through real-time feedback from synchronization protocols and timing measurements, the system maintains deterministic data delivery without requiring complex predetermined configurations for every scenario.
Data Source
AI summary
Time sensitive networking with data confidence is disclosed. Data ingested into a data confidence network is associated with annotations and/or confidence scores based on trust insertion technologies applied to the data. When time sensitive networking is applied, the annotations and confidence score reflect the application or use of time sensitive networking. Applications may determine whether to use or have confidence in the data based on the confidence score and/or annotations related to the use of time sensitive networking.