DocumentCode :
2989960
Title :
Efficient interoperation of user-generated geospatial model based on cloud computing
Author :
Lian Duan ; Baoqing Hu ; Xinyan Zhu
Author_Institution :
Geogr. Inf. Syst. Dept., Guangxi Teachers Educ. Univ., Nanning, China
fYear :
2012
fDate :
15-17 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
Numerous geospatial models have been developed. Development of technologies that facilitate sharing geospatial model becomes highly desirable. Although geospatial infrastructures built using standards-based distributed services have become the default computing paradigm adopted, most of them have been built following a top-down approach that only official providers are entitled to deploy and preserve geospatial resources including geospatial models. Since the mechanisms to deploy geospatial model as a web service in geospatial infrastructures are technologically complex, there has been limited participation from users, resulting in a scarcity of sharing geospatial model resources. Furthermore, the poor efficiency of geospatial model online implement remains the pains in most of geospatial infrastructures for transmitting and computing geodata in standard OGC service. Nowadays, the development of Cloud computing including associated spatial computing becomes the promising technology which is essential for enabling computing-intensive and data-intensive geospatial research and applications. Citizen sensing activities are accumulating data, information and models at a comparable or faster pace. To utilize these emerging technologies for addressing the limitations mentioned above, we present a distributed framework based on OGC specification and extend it with a service deploy component. This component improves ad hoc integration, deployment and register of geospatial model resources by two distinguishing approaches. Geospatial models can then be deployed, shared and accessed through tools and systems compliant with WPS by end users. Moreover, we modified the interface specification of WPS and WFS conforming to the MapReduce parallel computing mode and designed a self-adaptive task regulating mechanism for Hadoop and achieved great acceleration of the data-intensive computing in geospatial model. Finally, we illustrate our technique by the Geospatial Data and model pla- form addresses availability and efficiency of geospatial model auto-deploy mechanism.
Keywords :
cloud computing; geophysics computing; MapReduce parallel computing mode; OGC service; citizen sensing activities; cloud computing; data intensive eospatial research; interoperation; model efficiency; self adaptive task regulating mechanism; standards based distributed services; user generated geospatial model; web service; Adaptation models; Analytical models; Cloud computing; Computational modeling; Cloud computing; OGC; Parallel computing; User-driven; geospatial model; web processing service;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
Conference_Location :
Hong Kong
ISSN :
2161-024X
Print_ISBN :
978-1-4673-1103-8
Type :
conf
DOI :
10.1109/Geoinformatics.2012.6270296
Filename :
6270296
Link To Document :
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