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

doi:10.3976/j.issn.1002-4026.2018.03.002

山东科学 ›› 2018, Vol. 31 ›› Issue (3): 8-18.doi: 10.3976/j.issn.1002-4026.2018.03.002

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

宋苗苗，李文庆，王文彦，刘世萱，王晓燕，苗斌

齐鲁工业大学（山东省科学院），山东省科学院海洋仪器仪表研究所，山东省海洋监测仪器装备技术重点实验室，国家海洋监测设备工程技术研究中心，山东青岛 266001

收稿日期:2017-12-05 出版日期:2018-06-20 发布日期:2018-06-20
作者简介:宋苗苗(1985—)，女，助理研究员，博士，研究方向为网络地理信息系统、海洋地理信息系统、时空优化与分析、时空数据管理。E-mail：songmiaomiao_2006@126.com
基金资助:
山东省科学院青年基金(2015QN027)；山东省重点研发计划(2017GGX10131)

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

SONG Miao-miao, LI Wen-qing, WANG Wen-yan, LIU Shi-xuan, WANG Xiao-yan, MIAO Bin

Shandong Provincial Key Laboratory of Marine Monitoring Instrument Equipment Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, Institute of Oceanographic Instrumentation，Qilu University of Technology (Shandong Academy of Sciences) , Qingdao 266001, China

Received:2017-12-05 Online:2018-06-20 Published:2018-06-20

摘要/Abstract

摘要：

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。

关键词: 海洋监测数据, 分布式共享, 时空数据表达, 数据实时压缩传输, 网络地理信息系统

Abstract:

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.

Key words: ocean observing data, web geographical information system (GIS), distributed sharing, spatio-temporal data representation, data compression for real-time transmission

中图分类号:

TP311.56

宋苗苗，李文庆，王文彦，刘世萱，王晓燕，苗斌. 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[J]. 山东科学, 2018, 31(3): 8-18.

SONG Miao-miao, LI Wen-qing, WANG Wen-yan, LIU Shi-xuan, WANG Xiao-yan, MIAO Bin. Research on representation and transmission mode of ocean observing spatio-temporal data oriented to distributed sharing[J]. SHANDONG SCIENCE, 2018, 31(3): 8-18.

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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

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

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