The Study Of Key Technologies Of Spatial Analysis Services Based On G/S Model

With the development of spatial information technology, people’s demand for spatial information is increasing, and spatial analysis gradually developed from traditional C/S mode and B/S mode to G/S mode. In G/S mode, spatial analysis is built on the cloud in the form of services, provides spatial analysis services for industrial applications, this has a very important significance.Spatial analysis services in G/S mode involves two key issues:one is exchange standards of the spatial analysis cloud service, and another is collaborative computing of spatial analysis. G/S model takes HGML as service exchange standards, but now it is in the level of spatial data exchange, a complete spatial analysis cloud services interact standards is not formed; cloud computing is based on distributed file system, and realizes strategy that migration from calculation to storage, it is the effective solution of space analysis cloud service. Because spatial analysis is complex, so research and applications of cloud GIS are remain online space data services. Pointing for the current status, this article researched key technology of space analysis cloud services which based on G/S model.Firstly, investigate the characteristics of space analysis cloud services based on G/S model, and preliminary design a kind of space analysis cloud services infrastructure. The architecture is consisted of data registry center (G/S center server, task scheduling server cluster) and the storage cloud (spatial data server cluster). In this framework, network connections of spatial analysis cloud services is decided into cloud internal connection and cloud outside connection, and adopt different data communication technology to improve the efficiency of cloud services; adapts one interval run coding method for spatial data storage characteristics; to realize migration from calculation to storage, design storage structure of the vector data and raster data in the distributed file system. Secondly, one exchange standard of spatial analysis cloud services based on HGML was preliminary established. Based on defining basic data types of the spatial analysis, this paper had given three basic HGML commands of space analysis: GetCapabilities, DescribeFunction and ExecuteFunction. Standard framework made of these three commands can achieve standardization expression about spatial analysis services.Thirdly, designed and established Map/Reduce computing frame based on G/S mode. Analyzed and researched cloud computing parallel computing techniques Map/Reduce, To achieve a variety of modes polymerization of the G/S mode, designed Map/Reduce computing frame work in G/S mode, deeply investigate of the data load balancing scheduling and computational load balancing scheduling.Then put forward and established network map cloud services system in the G/S mode. Pointing to server bottleneck problem of web map service in traditional B/S mode, this paper established one network map cloud service infrastructure. On the base of given network map cloud service infrastructure, investigate the tasks division and task scheduling method of map services. And experiment verified the effectiveness of network map cloud services in G/S mode.Finally, pointing to the two aggregation modes which are the single point aggregation and multi polymerization spatial analysis mode, analysis task scheduling process of different polymerization mode. And elaborate task scheduling of single point aggregation according to space operations of geometry, spatial query based on WFS, grid computing in the server space data aggregation mode. Elaborate multi polymerization task scheduling technology according to spatial data cloud download, spatial interpolation of the client. Experiment results show that spatial analysis service based on G/S mode which established in this paper have enhanced the efficiency of spatial analysis service, and have a certain theoretical value and practical significance.The innovations of this paper are the following aspects:(1) Design infrastructure of space analysis cloud services based on G/S mode. The S end provide powerful spatial analysis cloud service capabilities for G end through the registered data center (central server, the task scheduling server farm) and the storage cloud (spatial data server cluster) collaboration; in this architecture, a spatial analysis client aggregation service classification is put forward:a single point aggregation and multi-point polymerization; presents an adaptive run-length encoding algorithm to improve the real-time nature of the cloud spatial data network transmission. Experiments show that the algorithm can guarantee compression rate while real-time compress spatial data streams.(2) Establish one space analysis cloud services exchange standards based on HGML, which rich the theoretical content demonstrated by G-end space data. Summarizes the spatial analysis cloud services exchange method by three simple commands; Execute command nesting making HGML have expression skills of complex spatial analysis model. Researching on exchange standards laid the language foundation for space analysis cloud service in G/S mode.(3) Proposed one Map/Reduce computing framework in G/S mode. The framework fully consider the multi polymerization manner in G/S mode, and can be run on the client, and can also be run in the central server and task scheduling node. It has Cross-end features, and improves the development and deployment efficient of spatial analysis module; in the framework, processing calculated dynamically balanced scheduling algorithm based on operation time, and proved the effectiveness of the algorithm; taking framework as the basis to design a network map cloud services based on G/S model, and proved the effectiveness of the Web Map Service in cloud computing environment.(4) Put forwarded one spatial data storage method in distributed file system. At the present distributed file system divided file block to sub-units by bytes, and it can’t effectively complete space analysis distribute calculate. So this paper built partitioning strategy and complete backup strategy for vector and raster data. Laid the data foundation for space analysis migration from calculate to storage.In this paper, a series of pioneering research and try of the spatial analysis are conducted. It can provide a theoretical reference for scientists in cloud services field and space analysis model developers, contribute to further improve and enrich of the G/S mode theory, and lead spatial analysis to depth development.