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A Service-Based Method for Multiple Sensor Streams Aggregation in Fog Computing

机译：雾计算中多个传感器流聚合的基于服务的方法

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摘要

A surge in sensor data volume has exposed the shortcomings of cloud computing, particularly the limitation of network transmission capability and centralized computing resources. The dynamic intervention among sensor streams also brings challenges for IoT applications to derive meaningful information from multiple sensor streams. To handle these issues, this paper proposes a service-based method with fog computing paradigm based on our previous service abstraction, which can capture meaningful events from multiple sensor streams. In our service abstraction, we utilize correlation analysis method to capture events as variations of correlation among sensor streams. Facing inconsistent frequency and shift of correlation, we propose a Dynamic Time Warping- (DTW-) based algorithm to obtain sensor streams' lag-correlation. For adaptively aggregating related events from different services, we also propose an event routing algorithm to assist the composition of cascaded events through service collaboration. This paper reports the tryout use of our method in Chinese power grid for detecting abnormal situations of power quality. Through a series of experiments based on real sensor data in power grid, we verified that our method can reduce the network transmission and computing resource with high accuracy.
机译：传感器数据量的激增暴露了云计算的不足，尤其是网络传输能力和集中计算资源的限制。传感器流之间的动态干预也给物联网应用程序从多个传感器流中获取有意义的信息带来了挑战。为了解决这些问题，本文在我们之前的服务抽象的基础上，提出了一种基于服务的方法，该方法采用雾计算范式，可以从多个传感器流中捕获有意义的事件。在我们的服务抽象中，我们使用相关性分析方法来捕获事件，作为传感器流之间相关性的变化。针对不一致的频率和相关偏移，我们提出了一种基于动态时间扭曲（DTW）的算法来获取传感器流的滞后相关。为了自适应地聚合来自不同服务的相关事件，我们还提出了一种事件路由算法，通过服务协作来辅助级联事件的合成。本文报告了我们的方法在中国电网中用于检测电能质量异常情况的试用情况。通过一系列基于电网中真实传感器数据的实验，我们验证了我们的方法能够以高精度减少网络传输和计算资源。

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    Zhongmei Zhang; Chen Liu; Shouli Zhang; Xiaohong Li; Yanbo Han;

  • 作者单位

    School of Computer Science and Technology Tianjin University;

    Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology;

    School of Computer Science and Technology Tianjin University;

    School of Computer Science and Technology Tianjin University;

    Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology;

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  • 正文语种 eng
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