工业互联网端边云协同数据同步方案设计与实现

传统的数据更新同步往往每次直接更新整个文件或不加选择地更新局部改动部分。后者虽然节约了一部分通信带宽,但是每次文件变化,不管变化多少都立即更新,增加了通信负荷,这两种方法均不能很好地满足工业互联网实时性要求。针对此问题,提出了一种工业互联网端边云协同数据同步方案。该方案通过计算差分文件进行阈值判断。若在阈值范围内,则将变化的数据块进行编码、压缩上传到对应的云存储节点中解压存储;否则将相关信息暂存在边缘层。通过和RS编码、Rsync差分算法的对比实验可知,该方案提高了更新数据传输效率,且通过编码压缩提高了安全性,性能整体优于其他方法。

Design and implementation of end-to-end cloud collaborative data synchronization scheme for industrial Internet

Traditional data update synchronization tends to update the entire file directly at a time or selectively update local changes. Although the latter method saves part of the communication bandwidth, but every time the file changes, no matter how much change is immediately updated, increasing the communication load, these two methods are not very good to meet the real-time requirements of the industrial Internet. Aiming at this problem, this paper proposed an end-to-end cloud collaborative data synchronization scheme for industrial Internet. In this scheme, it judged the threshold by calculating the difference file. If the value was within the threshold, the changed data blocks were encoded and compressed and uploaded to the corresponding cloud storage node for decompression storage. Otherwise, relevant information would be temporarily stored in the edge layer. Compared with RS encoding and Rsync differential algorithm, it can be seen that the proposed scheme improves the transmission efficiency of updated data, and improves the security through coding compression, and the overall performance is better than other methods.