面向分布式共享的海洋监测时空数据表达与传输模式研究

针对海洋时空监测数据分布式共享中的网络传输性能瓶颈问题，提出了一种基于共享式编码与实时压缩的时空数据表达与传输模式，建立了面向服务的海洋时空数据分布式共享框架，采用GML、KML、GeoJSON实现了海洋监测数据的编码式表达，采用压缩算法实现了数据实时高效传输。基于阿里云计算平台，设计和部署了面向海洋应用的分布式GIS系统作为实验平台，实验结果表明，采用GeoJSON和Deflate 6/GZIP建立海洋监测时空数据表达与传输模式，在分布式共享与集成系统中表现出较好的适用性和较突出的性能优势。

Research on representation and transmission mode of ocean observing spatio-temporal data oriented to distributed sharing

By focusing on the bottleneck of network transmission performance in the distributed sharing of ocean spatio-temporal monitoring data, the representation and transmission mode in distributed cloud computing environment was proposed to establish an efficient service-oriented sharing framework for ocean spatio temporal data. While adopting GML, KML and GeoJSON to encode ocean observing data, a data transmission mode based on real-time compression was proposed. The applicability of compression algorithms to ocean monitoring data enhanced the efficiency of data real-time transmission. Finally, based on the Ali cloud computing platform, a distributed GIS system for marine applications was designed and deployed as the testbed, and systematic experiments were conducted. The experimental results reveal that using the combination of GeoJSON and Deflate-6 / GZIP to establish the ocean observing spatio temporal data representation and transmission mode shows better applicability and more outstanding performance advantages in distributed sharing and integration system.