基于云计算的用户生成地理空间模型的高效互操作

Lian Duan, Baoqing Hu, Xinyan Zhu
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引用次数: 2

摘要

已经开发了许多地理空间模型。开发便于地理空间模型共享的技术是非常必要的。尽管使用基于标准的分布式服务构建的地理空间基础设施已成为采用的默认计算范例,但它们中的大多数都是按照自顶向下的方法构建的,只有官方提供商才有权部署和保存地理空间资源,包括地理空间模型。由于将地理空间模型作为web服务部署到地理空间基础设施中的机制在技术上是复杂的,用户的参与有限,导致地理空间模型资源共享的稀缺性。此外,在标准OGC服务中,地理空间模型的在线实现效率不高仍然是大多数地理空间基础设施传输和计算地理数据的痛点。如今,包括相关空间计算在内的云计算的发展成为一种有前途的技术,它对于实现计算密集型和数据密集型的地理空间研究和应用至关重要。公民感知活动正在以相当或更快的速度积累数据、信息和模型。为了利用这些新兴技术解决上面提到的限制,我们提出了一个基于OGC规范的分布式框架,并用服务部署组件对其进行扩展。该组件通过两种不同的方法改进了地理空间模型资源的临时集成、部署和注册。然后,最终用户可以通过符合WPS的工具和系统部署、共享和访问地理空间模型。此外,我们修改了符合MapReduce并行计算模式的WPS和WFS接口规范,并为Hadoop设计了自适应任务调节机制,实现了对地理空间模型中数据密集型计算的极大加速。最后,我们通过地理空间数据和模型平台说明了我们的技术,解决了地理空间模型自动部署机制的可用性和效率问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient interoperation of user-generated geospatial model based on cloud computing
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 platform addresses availability and efficiency of geospatial model auto-deploy mechanism.
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