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Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems ?

机译:回答传感器云系统中多源的最低成本质量意识查询?

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In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective.
机译:在基于传感器的系统中,对象的数据通常由多个来源提供。由于这些来源的数据质量可能不同,因此在查询观测值时,必须仔细选择来源,以确保访问高质量数据。一种解决方案是在云中执行质量评估,并选择可以回答查询的一组高质量,低成本数据源(即传感器或小型传感器网络)。本文研究了最低成本质量意识查询问题,该问题旨在以最小的成本从多源中找到高质量的结果。提供了查询结果的度量,并提出了两种回答最小成本质量意识查询的方法。还讨论了如何获得合理的参数设置。在现实生活中的数据实验证明,所提出的技术是有效的。

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