Continuous Distributed Top- Monitoring over High-Speed Rail Data Stream in Cloud Computing Environment

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.