Design and Implementation of Unloading Software for Data Integration and Storage
Xueya Liu, Shaoshi Wu, Dan Wang · 2024
As the volume of recorded data increases, there is an urgent need to improve data processing efficiency. The original software has poor fault tolerance and cannot handle certain types of anomalous data. In addition, when integrating data into the data center, it is necessary to obtain structured information about the data. The existing data unloading software can no longer meet the requirements for data integration and storage in the data center. In response to this, this paper redesigns the data distribution software to manage the streamlining of data from different recorders. It integrates various stages of data processing, including distribution and bitstream processing, to simplify the workflow. The software also prioritizes data distribution based on its priority level while obtaining the structured data information required for integration and storage.