Continuous Distributed Top-k Monitoring over High-Speed Rail Data Stream in Cloud Computing Environment. (5th December 2013)

• Record Type: Journal Article
• Authors: Wang, Hanning; Xu, Weixiang; Xu, Dongyan; Wei, Lili; Jia, Chaolong
• Other Names: Wang Fenyuan Academic Editor.
• Is Part Of: Advances in mechanical engineering. Volume 2013(2013)
• Publication Date: 2013-12-05
• Subjects: Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1155/2013/590234
• Languages: English
• ISSNs: 1687-8132

Abstract

Abstract : In the environment of cloud computing, real-time mass data about high-speed rail which is based on the intense monitoring of large scale perceived equipment provides strong support for the safety and maintenance of high-speed rail. In this paper, we focus on the Top-k algorithm of continuous distribution based on Multisource distributed data stream for high-speed rail monitoring. Specifically, we formalized Top-k monitoring model of high-speed rail and proposed DTMR that is the Top-k monitoring algorithm with random, continuous, or strictly monotone aggregation functions. The DTMR was proved to be valid by lots of experiments.