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Video transcoding scheme of multimedia data-hiding for multiform resources based on intra-cloud

机译:基于云内的多媒体数据隐藏多媒体数据的视频转码方案

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Recently, intra-cloud research has been actively conducted to reduce the waste of idle resources in distributed desktops and to increase resource utilization. Intra-cloud integrates the idle resources of distributed desktops to provide computing and storage services to users. Existing intra-cloud have only studied storage of large files and simple computing services. Research is needed for computing services of multimedia field such as video and audio in the intra-cloud. This paper proposes a diversify scheme for multiform video resources (DSMVR), which is a video transcoding scheme of multimedia data-hiding based on the parallel computing framework and the intra-cloud environment, in order to transcode for multiform resource types within the intra-cloud, which composed to computing infrastructure using legacy desktops. Its target users are community user groups within a certain size. By using a small-scale server group, parallel processing framework and improved task assignment algorithm, high-speed video transcoding can be realized by using ffmpeg, which is a vast software suite of libraries and programs designed for handling video, audio, and other multimedia files and streams, and different-definition videos are generated step by step at high speed. By using the DSMVR scheme, the size of a task can be dynamically analyzed in order to select the number of task processing servers required, thus ensuring the high scalability of the DSMVR. Thanks to these operations, the user can smoothly play videos at resolutions that are suitable for different smart devices.
机译:最近,已经积极进行了云内研究,以减少分布式桌面中空闲资源的浪费,并提高资源利用率。云内集成了分布式桌面的空闲资源,为用户提供计算和存储服务。现有的云内仅研究了大文件的存储和简单的计算服务。在云中的视频和音频等多媒体领域计算服务需要研究。本文提出了多种视频资源(DSMVR)的多样化方案,它是基于并行计算框架和云内环境的多媒体数据隐藏的视频转码方案,以便在内部内部用于多个圆形资源类型的转码云,组成用于计算基础架构的基础架构。其目标用户是一定大小的社区用户组。通过使用小规模的服务器组,并行处理框架和改进的任务分配算法,可以使用FFMPEG实现高速视频转码,这是一个庞大的软件套件,用于处理视频,音频和其他多媒体文件和流和不同定义视频以高速逐步生成。通过使用DSMVR方案,可以动态地分析任务的大小,以便选择所需的任务处理服务器的数量,从而确保DSMVR的高可扩展性。由于这些操作,用户可以在适合不同智能设备的分辨率下平滑播放视频。

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