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A novel temporal and spatial panorama stream processing engine on IoT applications
Journal of Industrial Information Integration ( IF 15.7 ) Pub Date : 2020-03-03 , DOI: 10.1016/j.jii.2020.100143
Yifan Yin , Boyi Xu , Hongming Cai , Han Yu

Nowadays, more and more streaming data are generated with the development of Internet of Things. Although, streaming data show great application values in practical scenarios, raw streams from terminal sensors are quite massive, heterogeneous and complex, and those features make it difficult for applications to deal with them. In order to simplify streaming data processing for applications, a novel temporal and spatial panorama stream processing engine is proposed. This stream processing engine forms an effective link between bottom sensors and upper stream-based applications, and provides configurable, flexible, available and usable stream services for various upper applications. With support of Internet plus and domain data, raw streaming data are formatted thorough data fusion and are represented in temporal, spatial, logic and storage views. Fusion data are encapsulated with multiple strategies and methods of clustering models on every dimension. According to configurable strategies, encapsulated data are extracted, partitioned and distributed as the form of dynamical variable gratitude data blocks into stream channels. Our engine is applied to a practical application scenario. Case study of dynamic power distribution application based on people crowd streaming data proves the customized service capabilities of our engine. And the outstanding performance of the engine is shown further by experiments evaluation in this case.



中文翻译:

基于物联网应用的新型时空全景流处理引擎

如今,随着物联网的发展,产生了越来越多的流数据。尽管流数据在实际场景中显示出巨大的应用价值,但来自终端传感器的原始流却非常庞大,异构且复杂,并且这些功能使应用程序难以处理它们。为了简化应用程序的流数据处理,提出了一种新颖的时空全景流处理引擎。该流处理引擎形成了底部传感器和基于上游的应用程序之间的有效链接,并为各种上部应用程序提供了可配置,灵活,可用和可用的流服务。在Internet plus和域数据的支持下,原始流数据通过数据融合进行了格式化,并以时间,空间,逻辑和存储视图表示。融合数据通过在各个维度上采用多种策略和方法进行聚类模型封装。根据可配置的策略,将封装的数据作为动态变量折衷数据块的形式提取,分区和分发到流通道中。我们的引擎已应用于实际应用场景。基于人群流数据的动态配电应用案例研究证明了我们引擎的定制服务能力。在这种情况下,通过实验评估进一步显示了发动机的出色性能。以动态变量谢意数据块的形式进行分区和分发到流通道中。我们的引擎已应用于实际应用场景。基于人群流数据的动态配电应用案例研究证明了我们引擎的定制服务能力。在这种情况下,通过实验评估进一步显示了发动机的出色性能。以动态变量谢意数据块的形式进行分区和分发到流通道中。我们的引擎已应用于实际应用场景。基于人群流数据的动态配电应用案例研究证明了我们引擎的定制服务能力。在这种情况下,通过实验评估进一步显示了发动机的出色性能。

更新日期:2020-03-03
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