云中的地质流

Seyed Jalal Kazemitabar, F. Kashani, D. McLeod
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引用次数: 17

摘要

近年来,地理空间数据库已实现商业化,并广泛面向广大用户。当前数据生成和查询率的指数级增长突出了高效流技术的重要性。传统的数据库技术以持久性和低动态性的数据对象为基础,不能满足高效的地理空间数据流的要求。地理流是数据流处理和地理空间查询的交叉点,是该领域正在进行的研究热点。在本文中,我们描述了为什么云是支持地理空间流数据处理的最合适的基础设施。首先,我们认为云最适合大规模地理流应用程序的需求。其次,我们提出了ElaStream,这是一种通用的基于云的流基础设施,通过分而治之和结合范例实现了巨大的并行性。第三,我们研究了数据流和(地理)空间数据库领域的关键相关工作,并描述了构建可扩展的基于云的地理流应用所面临的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geostreaming in cloud
In recent years, geospatial databases have been commercialized and widely exposed to mass users. Current exponential growth in data generation and querying rates for these data highlights the importance of efficient techniques for streaming. Traditional database technology, which operates on persistent and less dynamic data objects does not meet the requirements for efficient geospatial data streaming. Geostreaming, the intersection of data stream processing and geospatial querying, is an ongoing research focus in this area. In this paper, we describe why cloud is the most appropriate infrastructure in which to support geospatial stream data processing. First, we argue that cloud best fits the requirements of a large-scale geostreaming application. Second, we propose ElaStream, a general cloud-based streaming infrastructure that enables huge parallelism by means of the divide, conquer, and combine paradigm. Third, we examine key related work in the data streaming and (geo)spatial database fields, and describe the challenges ahead to build scalable cloud-based geostreaming applications.
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