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Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems.
Li, Mohan; Sun, Yanbin; Jiang, Yu; Tian, Zhihong.
Affiliation
  • Li M; Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China. limohan@gzhu.edu.cn.
  • Sun Y; Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China. sunyanbin@gzhu.edu.cn.
  • Jiang Y; Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China. jiangyu@gzhu.edu.cn.
  • Tian Z; Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China. tianzhihong@gzhu.edu.cn.
Sensors (Basel) ; 18(12)2018 Dec 18.
Article in En | MEDLINE | ID: mdl-30567395
ABSTRACT
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.
Key words

Full text: 1 Database: MEDLINE Type of study: Health_economic_evaluation Language: En Year: 2018 Type: Article

Full text: 1 Database: MEDLINE Type of study: Health_economic_evaluation Language: En Year: 2018 Type: Article