Buffer Memory Digital Stuffing Data Time Interval Precision
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Solution Overview
Problem
Existing methods for modeling delay fluctuations in data transmission networks lack sufficient timing resolution, making it difficult to accurately set time intervals between data frames according to a pre-determined probability distribution, especially at high speeds, which is crucial for testing data transmission systems and Circuit Emulation Service quality.
Innovation Solution
A method and arrangement that utilize a buffer memory to insert digital stuffing data between data frames, where the bit quantity of the stuffing data is calculated based on the target time interval length, allowing for precise adjustment of time intervals without real-time start and end procedures, achieving sub-nanosecond resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a processor-controlled timer is used to define time intervals between data frames, then the timing can be adjusted, but the timing resolution is limited to roughly 125 μs with typical PC processors
Solution Approach 1:
The patent replaces the processor-controlled timer mechanism with a bit-level data manipulation approach. Instead of using hardware timers with limited resolution, the invention inserts calculated quantities of bit sequences (stuffing data) into the data stream, where the time interval is determined by the duration required to transmit a specific number of bits at the known data rate. This substitution achieves nanosecond-level precision without requiring high-frequency processors.
Solution Approach 2:
The invention changes the fundamental parameter for controlling time intervals from timer clock cycles to bit quantities. By calculating the required time interval based on the data transmission rate and inserting a corresponding number of bits as stuffing data, the system achieves precise timing control. The formula T = N/R (where T is time interval, N is bit quantity, and R is data rate) enables accurate time interval adjustment without relying on processor timing capabilities.
2Measurement precision
If high clock frequencies and powerful processors are used to achieve denser timing resolution, then the timing precision improves, but the apparatus becomes expensive
Solution Approach 1:
The patent uses inexpensive bit sequences (stuffing data) as disposable elements to achieve precise timing. Instead of investing in expensive high-performance processors, the invention inserts calculated quantities of simple bit patterns into the data stream. These bit sequences serve as temporary placeholders that define time intervals through their transmission duration, providing high-precision timing control using low-cost computational resources.
3Measurement precision
If digital stuffing data is inserted between data frames to define time intervals, then precise timing control is achieved, but the data stream structure becomes more complex
Solution Approach 1:
The patent introduces digital stuffing data as an intermediary element between actual data frames. These stuffing sequences serve as mediators that define time intervals without interfering with the primary data transmission function. The calculation unit determines the appropriate quantity of stuffing bits based on the desired time interval and data rate, and the insertion unit places them in the data stream, creating a clear separation between timing control and data processing functions.
Data Source
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AI summary
The invention relates to producing data traffic where the time intervals between successive data frames follow a predetermined probability distribution. In the present invention, it is surprisingly discovered that a time interval of a desired length between successive data frames can be produced by setting a certain bit quantity of digital stuffing data, defined on the basis of the target length of the time interval target, in a buffer memory (101), where successive data frames are waiting to be transmitted. The digital stuffing data is set in the buffer memory (101), so that the stuffing data is, in the read-out order, located between successive data frames.