A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure

For geospatial cyberinfrastructure-enabled web services,the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection,response and decision-making.Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications,their rich geometry and property information facilitates the development of interactive,efficient and intelligent data analysis and visualization applications.However,the big-data issues of vector datasets have hindered their wide adoption in web services.In this research,we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing.This strategy combines:(1)pre-and on-the-fly generalization,which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency;(2)a progressive attribute transmission method to reduce data size and,therefore,the service response time;(3)compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments.A cyberinfrastructure web portal was developed for implementing the proposed technologies.After applying our optimization strategies,substantial performance enhancement is achieved.We expect this work to facilitate real-time spatial feature sharing,visual analytics and decision-making.