Spatial Data Management in IoT systems: A study of available storage and indexing solutions

Maria Krommyda, Verena Kantere
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引用次数: 3

Abstract

As the Internet of Things (IoT) systems gain in popularity, an increasing number of Big Data sources are available. Ranging from small sensor networks designed for household use to large fully automated industrial environments, the Internet of Things systems create billions of measurements each second making traditional storage and indexing solutions obsolete. While research around Big Data has focused on scalable solutions that can support the datasets produced by these systems, the focus has been mainly on managing the volume and velocity of these data, rather than providing efficient solutions for their retrieval and analysis. A key characteristic of these data, which is, more often than not, overlooked, is the spatial information that can be used to integrate data from multiple sources and conduct multidimensional analysis of the collected information. We present here the solutions currently available for the storage and indexing of spatial datasets produced by the IoT systems and we discuss their applicability in real world scenarios.
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物联网系统中的空间数据管理:可用存储和索引解决方案的研究
随着物联网(IoT)系统的普及,越来越多的大数据源可用。从为家庭使用而设计的小型传感器网络到大型全自动工业环境,物联网系统每秒产生数十亿次测量,使传统的存储和索引解决方案过时。虽然围绕大数据的研究主要集中在可扩展的解决方案上,这些解决方案可以支持这些系统产生的数据集,但重点主要集中在管理这些数据的数量和速度上,而不是为它们的检索和分析提供有效的解决方案。这些数据的一个往往被忽视的关键特征是空间信息,可用于整合来自多个来源的数据并对收集到的信息进行多维分析。我们在这里介绍了目前可用于存储和索引物联网系统产生的空间数据集的解决方案,并讨论了它们在现实世界场景中的适用性。
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