Distributed Analysis Device Time Synchronization via Pseudo Frames
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for recording, synchronizing, and analyzing data in spatially dispersed communications networks face challenges in achieving precise time synchronization across multiple analysis units, leading to inefficiencies and increased costs due to the need for absolute time stamps and limited time resolution in standard operating systems.
Innovation Solution
The method involves ignoring the absolute times of analysis units and using a synchronization signal to insert 'pseudo frames' between data frames, allowing for simultaneous time synchronization of data files across units, utilizing publicly available signals like GPS or DCF for high precision at lower costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If absolute time stamps are used for synchronizing data from spatially dispersed analysis units, then time synchronization precision is improved, but system cost increases substantially
Solution Approach 1:
A central synchronization server acts as an intermediary to distribute time synchronization information to dispersed analysis units. Instead of each unit independently obtaining expensive absolute time stamps, the server mediates the synchronization process by collecting time information from a common reference source and distributing it efficiently, thereby reducing overall system cost while maintaining precision.
Solution Approach 2:
The synchronization server performs multiple functions: it collects time information from various sources, processes synchronization data, and distributes it to multiple analysis units simultaneously. This universal approach replaces the need for each analysis unit to independently acquire expensive absolute time stamps, reducing system cost while maintaining synchronization precision across all units.
2Ease of operation
If standard operating systems are used for data recording, then ease of operation is improved, but time resolution is limited
Solution Approach 1:
The synchronization server acts as an intermediary that bridges standard operating systems and high-precision timing requirements. It collects time information from reliable sources, processes it into appropriate time stamps, and provides this enhanced timing information to analysis units running on standard operating systems, thereby maintaining ease of operation while achieving high time resolution.
Solution Approach 2:
The system replaces the mechanical timing limitations of standard operating systems with a centralized synchronization mechanism that uses networked time information. Instead of relying on the internal clocks of individual OS instances, the system substitutes a network-based time synchronization approach that provides superior time resolution while keeping the OS layer simple and easy to operate.
3Adaptability or versatility
If multiple analysis units are dispersed spatially in a communication network, then adaptability is improved, but achieving precise time synchronization becomes more difficult
Solution Approach 1:
The time synchronization function is segmented and centralized in a separate synchronization server that operates independently from the analysis units. This segmentation allows analysis units to be dispersed spatially across the network while the server maintains a centralized role in coordinating time synchronization, thereby preserving both spatial adaptability and synchronization precision.
Solution Approach 2:
The synchronization server continuously collects time information from reliable sources and distributes updated synchronization data to analysis units. This feedback mechanism ensures that dispersed analysis units maintain precise time synchronization despite spatial separation, as the server continuously adjusts and updates time information based on current network conditions and reference sources.
Data Source
AI summary
A method and a system for recording, synchronizing and analyzing data transmitted between spatially distributed devices of a communication network using spatially distributed analysis devices, wherein the data are received by at least two analysis devices looped into the communication network, and wherein the received data are marked by means of a synchronization signal which is simultaneously received by the analysis devices. In order to simplify the recording, synchronization and analysis of data by means of spatially distributed analysis devices, provision is made for the analysis devices to store data frames of the received data in data files, wherein each received data frame is marked with a time stamp of a local time of the receiving analysis device, and wherein time synchronization events are produced by means of the received synchronization signal in each of the analysis devices.