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Towards Improving Query Performance of Web Feature Services (WFS) for Disaster Response

机译:致力于提高Web功能服务(WFS)的灾难响应查询性能

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While OGC’s WFS facilitates disseminating heterogeneous spatial data over the Web and allows feature-level geospatial information sharing and synchronization, performance issues challenge the efficient and effective utilization of WFS for disaster response. Literature shows that obtaining spatial information becomes very slow when querying WFS systems from large geospatial databases over the Internet. Solutions on how to improve the WFS system performance so that spatial data can be delivered to disaster responders within a reasonable amount of time are needed. This paper proposes a parallel approach based on Voronoi diagram indexing and data/task parallelism for improving the query performance of WFS systems for disaster applications. Experimental results show that the parallel approach can significantly improve the response time needed to process the spatial queries from a massive volume of spatial data for disaster response.
机译:OGC的WFS有助于通过Web分发异构空间数据,并允许要素级地理空间信息共享和同步,而性能问题则挑战了WFS高效,有效地用于灾害响应的能力。文献表明,当通过Internet从大型地理空间数据库查询WFS系统时,获取空间信息变得非常缓慢。需要有关如何提高WFS系统性能以使空间数据可以在合理的时间内交付给灾难响应者的解决方案。本文提出了一种基于Voronoi图索引和数据/任务并行性的并行方法,以提高WFS系统在灾难应用中的查询性能。实验结果表明,并行方法可以显着提高处理来自大量空间数据以进行灾难响应的空间查询所需的响应时间。

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