Review on Data Error Detection Methods in Distributed Storage Mode
Data error detection is an important part of data quality assurance,which is directly related to the reliability of data lifecycle analysis results.With the gradual expansion of the application field and scope of the cloud-edge data center architecture,and the improvement of the storage and computing pow-er of network nodes,distributed local storage of data is becoming more and more common.The data error detection method under the traditional data centralized storage mode is difficult to adapt to the data dis-tributed storage mode.Based on this,this paper carries out a survey of data error detection methods in distributed storage mode.On the basis of the description and classification of data error detection prob-lems,this paper summarizes and analyzes data error detection methods based on traditional distributed learning and data error detection methods on account of federated learning framework from the perspec-tives of technical principles,model methods and main progress.The differences and connections between them are compared,and the potential research opportunities and concerns in the field are prospected.This paper provides reference for data error detection and related research in distributed storage mode.
万方数据
维普
