Geoprocessing in Cloud Computing platforms-a comparative analysis  

作　　者：Peng Yue Hongxiu Zhou Jianya Gong Lei Hu 

机构地区：[1]State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing(LIESMARS),Wuhan University,Wuhan,China

出　　处：《International Journal of Digital Earth》2013年第4期404-425,共22页国际数字地球学报（英文）

基　　金：This work was funded jointly by National Basic Research Program of China(2011CB707105);Project 41271397 and 41023001 supported by NSFC;LIESMARS(Wuhan University)Special Research Funding.

摘　　要：The emergence of Cloud Computing technologies brings a new information infrastructure to users.Providing geoprocessing functions in Cloud Computing platforms can bring scalable,on-demand,and cost
effective geoprocessing services to geospatial users.This paper provides a comparative analysis of geoprocessing in Cloud Computing platforms
Microsoft Windows Azure and Google App Engine.The analysis compares differences in the data storage,architecture model,and development environment based on the experience to develop geoprocessing services in the two Cloud Computing platforms;emphasizes the importance of virtualization;recommends applications of hybrid geoprocessing Clouds,and suggests an interoperable solution on geoprocessing Cloud services.The comparison allows one to selectively utilize Cloud Computing platforms or hybrid Cloud pattern,once it is understood that the current development of geoprocessing Cloud services is restricted to specific Cloud Computing platforms with certain kinds of technologies.The performance evaluation is also performed over geoprocessing services deployed in public Cloud platforms.The tested services are developed using geoprocessing algorithms from different vendors,GeoSurf and Java Topology Suite.The evaluation results provide a valuable reference on providing elastic and cost-effective geoprocessing Cloud services.

关 键 词：GEOPROCESSING Cloud computing geospatial service GIS Microsoft Azure Google App Engine 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]