A solution for real-time web collaborative visualization of trend data

With the development of web technology, collaborative applications provide a platform for geographically dispersed users to data analysis in numerous domains. However, the data delay hinders the collaborative teamwork under the circumstance of unstable network environment. In order to reduce the latency of collaborative web visualization, this paper proposes a solution for visualization of trend data. According to the network environment, the solution choose different algorithm to compress data. When the network environment is not good, the data scale in the transmission process is reduced by lossless compression. When the network environment is bad, the data is compressed by a modified neural network classification algorithm. The compression data is sent to users by the low-cost server push technology after compression. The solution improves the real-time performance of collaborative visualization and reduces the delay due to the network problem.