DQS-Cloud:用于传感器服务的数据质量感知自主云

Abhishek Kothari, Vinay Boddula, Lakshmish Ramaswamy, Neda Abolhassani
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引用次数: 16

摘要

随着物联网时代的到来,域感知领域的服务化程度越来越高。为了有效地支持这种服务化,越来越需要一个功能强大且易于使用的基础设施,以实现传感器数据的实时无缝共享。在本文中,我们提出了数据质量感知传感器云(DQS-Cloud)的设计和评估,这是一种基于云的传感器数据服务基础设施。DQS-Cloud具有三个新特点。首先,从feed发现到故障恢复,数据质量在整个基础设施中无处不在。其次,它结合了基于自主计算的技术来处理传感器故障以及数据质量动态。第三,DQS-Cloud还具有独特的传感器流管理引擎,通过动态放置流管理操作符来优化系统性能。本文通过几个实验来研究该框架的有效性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DQS-Cloud: A Data Quality-Aware autonomic cloud for sensor services
With the advent of Internet of Things, the field of domain sensing is increasingly being servitized. In order to effectively support this servitization, there is a growing need for a powerful and easy-to-use infrastructure that enables seamless sharing of sensor data in real-time. In this paper, we present the design and evaluation of Data Quality-Aware Sensor Cloud (DQS-Cloud), a cloud-based sensor data services infrastructure. DQS-Cloud is characterized by three novel features. First, data-quality is pervasive throughout the infrastructure ranging from feed discovery to failure resilience. Second, it incorporates autonomic-computing-based techniques for dealing with sensor failures as well as data quality dynamics. Third, DQS-Cloud also features a unique sensor stream management engine that optimizes the system performance by dynamically placing stream management operators. This paper reports several experiments to study the effectiveness and the efficiency of the framework.
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