VideoCoreCluster: Energy-Efficient, Low-Cost, and Hardware-Assisted Video Transcoding System

Abstract

Video streaming is one of the killer applications in recent years. Video transcoding plays an important role in the video streaming service to cope with the various purposes. Specifically, content owners and publishers heavily utilize video transcoders to reconfigure source video in a variety of formats, video qualities, and bitrate to provide end users with the best possible quality of service. In this paper, we present VideoCoreCluster, a low-cost and energy-efficient transcoder cluster that is suitable for live streaming services. We designed and implemented real-time video transcoder cluster using cheap ($35), powerful, and energy-efficient Raspberry Pi. The quality of transcoded video provided by VideoCoreCluster is similar to the best software-based video transcoder while consuming significantly less energy (<3 W). We have proposed a scheduling algorithm based on priority of video stream and transcoding capacity. Our cluster manager provides reliable and scalable streaming services, because it uses the characteristics of adaptive bitrate scheme. We have deployed our transcoding cluster to provide IP-based TV streaming services on our university campus.