Hadoop MapReduce and Dynamic Intelligent Splitter for Efficient and Speed transmission of Cloud-based video transforming
Cloud-based video transmission includes the multimedia data with variant specifications in mobile devices. Video transforming contains the vital role in video streaming for media communication. The main problem with transforming of video is that it needs much time for producing the quality output. Transforming needs the data to alter the video in the necessary transformation and this kind of procedure will continue in a dynamic manner to improve the progress. This work proposes a dynamic video splitter that includes the Hadoop MapReduce algorithm to improve the efficiency within the limited time. The main performance parameters are Video Deformation, Frame enslavement. The experimental analysis suggested that the proposed work considerably improved compared to related works and also it transmits maximized quality of video with minimized video deformation.
Cloud Computing, Hadoop, MapReduce, Video Transforming, Encoding, PSNR