Abstract
In sensor-cloud systems, a common scenario is that more than one sources can provide the data of the same object. 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. Experiments on real-life data verified that the proposed techniques are effective.
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Acknowledgments
The work is supported by the National Natural Science Foundation of China (No. 61871140, 61702220, 61702223, 61572153) and the National Key Research and Development Plan (Grant No. 2018YFB0803504).
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Li, M., Jiang, Y., Sun, Y., Tian, Z. (2018). Answering the Min-Cost Quality-Aware Query on Multi-sources in Sensor-Cloud Systems. In: Wang, G., Chen, J., Yang, L. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2018. Lecture Notes in Computer Science(), vol 11342. Springer, Cham. https://doi.org/10.1007/978-3-030-05345-1_13
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