Mesh Network Clock Syntonization for Drift Error Correction
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Solution Overview
Problem
Existing clock synchronization technologies face limitations in achieving nanosecond-level accuracy due to frequency drift and require expensive specialized hardware, leading to inefficiencies and unfair processing in networked systems.
Innovation Solution
A system using network observations and adaptive stochastic control to estimate and correct clock frequency and offset, ensuring synchronization accuracy within nanoseconds without additional hardware, utilizing commodity clocks and advanced filtering techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized atomic clock synchronization is used, then time synchronization accuracy is improved, but system vulnerability to single-point failures increases and scalability is limited
Solution Approach 1:
The patent divides the centralized time synchronization system into distributed autonomous clock segments, where each clock operates independently as a separate unit. This segmentation eliminates the single-point failure vulnerability of centralized systems while maintaining synchronization accuracy through peer-to-peer comparisons between distributed clock segments.
Solution Approach 2:
The patent introduces virtual reference clocks and comparison algorithms as intermediaries that enable autonomous clocks to synchronize with each other without direct physical connection to a central authority. These virtual intermediaries facilitate accurate time synchronization while preserving the distributed architecture's reliability advantages.
2Measurement precision
If more atomic clocks are deployed to improve synchronization accuracy, then time synchronization precision is improved, but system complexity and cost increase
Solution Approach 1:
Each autonomous clock in the distributed system performs self-synchronization by comparing its time with neighboring clocks and automatically adjusting its own operation. This self-service capability eliminates the need for complex centralized control mechanisms, allowing the system to scale by simply adding more independent clock units without proportionally increasing system complexity.
Solution Approach 2:
The patent combines multiple autonomous clock operations into a unified distributed synchronization network where clocks collectively achieve higher precision through statistical averaging and redundancy. This merging approach improves precision while keeping individual clock units simple and modular.
3Reliability
If autonomous clocks operate independently without synchronization, then system reliability is improved, but time synchronization accuracy deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where autonomous clocks continuously compare their time with neighboring clocks and receive correction signals. This feedback loop maintains synchronization accuracy while preserving the independence and reliability of individual clock units, as each clock autonomously adjusts based on local comparisons rather than centralized control.
Solution Approach 2:
The system dynamically adjusts the synchronization behavior of autonomous clocks based on local conditions and network state. Each clock can independently modify its synchronization parameters and comparison frequency, allowing the system to maintain accuracy while adapting to changing conditions without compromising reliability.
Data Source
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AI summary
Systems and methods are disclosed herein for syntonizing machines in a network. A coordinator accesses probe records for probes transmitted at different times between pairs of machines in the mesh network. For different pairs of machines, the coordinator estimates the drift between the pair of machines based on the transit times of probes transmitted between the pair of machines as indicated by the probe records. For different loops of at least three machines in the mesh network, the coordinator calculates a loop drift error based on a sum of the estimated drifts between pairs of machines around the loop and adjusts the estimated absolute drifts of the machines based on the loop drift errors. Here, the absolute drift is defined relative to a drift of a reference machine.