Dynamic scheduling on video transcoding for MPEG DASH in the cloud environment

Abstract

The Dynamic Adaptive Streaming over HTTP (referred as MPEG DASH) standard is designed to provide high quality of media content over the Internet delivered from conventional HTTP web servers. The visual content, divided into a sequence of segments, is made available at a number of different bitrates so that an MPEG DASH client can automatically select the next segment to download and play back based on current network conditions. The task of transcoding media content to different qualities and bitrates is computationally expensive, especially in the context of large-scale video hosting systems. Therefore, it is preferably executed in a powerful cloud environment, rather than on the source computer (which may be a mobile device with limited memory, CPU speed and battery life). In order to support the live distribution of media events and to provide a satisfactory user experience, the overall processing delay of videos should be kept to a minimum. In this paper, we propose a novel dynamic scheduling methodology on video transcoding for MPEG DASH in a cloud environment, which can be adapted to different applications. The designed scheduler monitors the workload on each processor in the cloud environment and selects the fastest processors to run high-priority jobs. It also adjusts the video transcoding mode (V TM) according to the system load. Experimental results show that the proposed scheduler performs well in terms of the video completion time, system load balance, and video playback smoothness. Copyright 2014 ACM.