Research On Spatial Information Services Cloud For Data Granularity In G/S Model

Emerging applications of the rising of the massive effective data transmissionhas become a more serious problem, because the data in the spatial informationservices cloud has massive, multi-source, unstructured, and real-time characteristics.Thus, spatial data has a complex structure in types and formats, and therefore how toaccomplish the efficient transfer tasks of spatial in the network is an important task onthe spatial information services cloud.In view of this situation, this thesis has researched the data types andcharacteristics in the spatial information services, which is based on the nationalnatural science fund project “the client aggregation services of spatial informationweb services model” and in order to transfer mass data in different networkenvironment as a breakthrough point in spatial information services cloud. And indifferent network environment, we have designed three the best particle models ofspatial data for test, and then we have analyzed the impact parameters of the testresults, defined a set of using data granularity method based on DGML, finally wehave tested three different reasonable granularity of data under the different networkenvironment. The achievements this article has gained include:(1) Studied of the data characteristics and type in the spatial information servicescloud.Proceed with the spatial information of data characteristics and the type of thedata, and combined with the spatial information in the emerging applicationcharacteristics, we have enriched the massive spatial data characteristics and the typeof the data, and we have systematically and comprehensively introduced all kinds ofdata partition bases, function and scope of application through analyzing all kinds ofspatial information data of heterogeneous characteristics, spatial characteristics, timecharacteristics and so on, it has provided academic basis for the study of datatransmission in the process of the granularity.(2) Designed the test model of data granularity in different network environmentfor spatial information services cloud.Though the study of the data sending and receiving algorithm, we have put forward a set of the test model for data granularity in spatial information datatransmission, and we have used the corresponding test model method according to thedifferent network environment design, it has provided a theoretical basis and testmodel in the test link which is based on the comprehensive consideration of multiplepossible influence factor on test results.(3) Designed a set of scheduling method using data granularity based on DGMLApplied to data transmission of data granularity depends on the choice oftransmission network status and data features, in order to realize the data granularityadaptive dynamic selection, this thesis has designed a kind of data granularitydescription method based on XML-data granularity markup language DGML(Data-Granularity Markup Language). Through the DGML multilayer markers ofgrammatical structure, the data characteristics and network environment can havebeen unified descripted in the data transmission, which provides a basis of theadaptive dynamic matching the appropriate granularity of data.(4) Tested out the best data granularity in each kind of network environment fordata transmission.According to the previous design under the different network environment modelfor different scale test, we have recorded the completion time of the different datagranularity for data transmission, and the test result would have been generated visualdiagrammatic form to facilitate the observation of the analysis. Last the results areanalyzed and given in each case for data transmission of the best data granularity. Ithas a certain practical value for the spatial information services in different types ofspatial data efficiently in the network transmission.Based on the innovative research mentioned above, the achievements this articlehas gained include:(1) Proposed three test model of data granularity in different networkenvironment for spatial information services cloud.Though the study of the data sending and receiving algorithm, we have putforward a set of the test model for data granularity in spatial information datatransmission, and according to the different environment design, we have used thecorresponding test methods, Considering several factors that may affect the datatransmission, we have obtained the optimal granularity which applied to datatransmission under different conditions through a variety of different data granularityof speed and efficient analysis.(2) Proposed a data granularity markup language DGML for management andscheduling use.Applied to data transmission of data granularity depends on the choice oftransmission network status and data features, in order to realize the data granularityadaptive dynamic selection, this thesis has designed a kind of data granularitydescription method based on XML-data granularity markup language DGML (Data-Granularity Markup Language). Through the DGML multilayer markers ofgrammatical structure, the data characteristics and network environment can havebeen unified descripted in the data transmission, which provides a basis of theadaptive dynamic matching the appropriate granularity of data.