The Research About Stream Media Surveillance System Based On Cloud Computing

Stream media surveillance system is the most popular network surveillance solution.Along with the development of Intelligent City, the stream media surveillance system, whichis the core of Intelligent City, is now under high pressure. First point is the mass storage, mostof the smart application, for example, the Intelligent Traffic and Intelligent Community, areall based on the surveillance system, so how to store the mass monitoring data from thecameras all over the city is unavoidable; Second is how to deal with the mass video data, withthe rAPId spread of the smartphones and other smart terminals, people want to visit thesurveillance systm whenever and wherever possible, the monitoring data need to be transformto various kinds of video formats the smartphone supported. Therefore, how to combine thestream media surveillance system with the distributed cluster is the main content of this paper.This paper promotes a new architecture which combines the popular stream mediasurveillance system with the Hadoop, and designs a number of experiments to verify thefeasibility of the new system. The main work of this paper is below:(1) introduce the keytechnology used in new system, including Hadoop, fuse middleware, Hive, R language andstream media server;(2) describes the lack of the present stream media surveillance system toface the rAPId development of mobile internet;(3) promotes a new architecture combines thethe present stream media surveillance system with the Hadoop, including shielding thedifference between ordinary file system and distributed file system through fuse middleware,so the stream media server can use Hadoop without any change; combines R language withHive, to lay the foundation of mass data analysis in the future;(4) describes some possiblescenes of the system, and verifies the effectiveness of system through a number ofexperiments, including I/O performance test of distributed file system, stream media playingtest and some fundamental data analysis based on RHive.