Mesh Network Clock Syntonization Using Loop Drift Correction
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Solution Overview
Problem
Current clock synchronization methods in networked systems, such as data centers and distributed ledgers, face limitations in achieving high accuracy due to frequency drift caused by environmental factors, leading to inefficiencies and fairness issues, with existing solutions requiring expensive specialized hardware and often settling for millisecond-level accuracy rather than nanosecond-level synchronization.
Innovation Solution
The implementation of a system that uses a coordinator to continuously estimate and adjust clock offset and frequency drift using network observations and advanced filtering techniques, allowing for precise synchronization of clocks to within nanosecond accuracy without the need for additional hardware, by employing a reference clock and adaptive stochastic control to maintain synchronization within defined bounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized hardware is used to achieve nanosecond-level clock synchronization, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces specialized hardware mechanisms with software-based algorithms. Specifically, it uses software implementations of PTP protocol processing, clock offset calculation algorithms, and frequency drift compensation mechanisms to achieve nanosecond-level synchronization without requiring specialized hardware components throughout the network.
Solution Approach 2:
The patent uses software copies and simulations of precision timing mechanisms. It implements virtual clock models and software-based time stamping systems that replicate the functionality of hardware precision clocks, allowing standard commodity hardware to achieve high-precision synchronization through software intelligence.
2Device complexity
If millisecond-level synchronization algorithms are used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent fundamentally changes the time parameter from millisecond-level to nanosecond-level precision. It achieves this by implementing high-resolution time stamping, using frequency drift compensation algorithms, and applying clock offset corrections at the nanosecond scale, thereby transforming standard algorithms into high-precision synchronization solutions.
Solution Approach 2:
The patent implements continuous feedback mechanisms where clock offsets and frequency drifts are constantly measured and corrected. It uses round-trip time measurements, one-way time stamping, and iterative correction algorithms that provide real-time feedback to maintain nanosecond-level synchronization accuracy without requiring specialized hardware.
3Stability of the object's composition
If clock syntonization is performed using traditional methods, then frequency matching is improved, but cost and device complexity increase
Solution Approach 1:
The patent replaces hardware-based frequency stabilization mechanisms with software-based frequency drift compensation. It uses algorithms that continuously monitor and adjust clock frequencies based on observed drift patterns, eliminating the need for specialized frequency-stabilized hardware components.
Solution Approach 2:
The patent implements dynamic frequency adjustment where clock frequencies are continuously adapted based on real-time measurements of drift and offset. This dynamic approach allows the system to compensate for environmental factors and maintain frequency stability through software control rather than static hardware design.
Data Source
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.