MMDec 1, 2020

Cost Efficient Repository Management for Cloud-Based On-Demand Video Streaming

arXiv:2012.00597v123 citations
AI Analysis

This research offers a cost-saving solution for cloud-based video streaming providers by optimizing video transcoding and storage, particularly beneficial for those managing large video repositories with long-tail access patterns.

This paper addresses the high storage and computational costs associated with pre-transcoding all video formats for cloud-based on-demand video streaming. The authors propose a hybrid approach that partially pre-transcodes videos and transcodes the remainder on-demand, achieving up to a 70% cost reduction in repositories with frequently accessed videos.

Video transcoding is the process of converting a video to the format supported by the viewer's device. Video transcoding requires huge storage and computational resources, thus, many video stream providers choose to carry it out on the cloud. Video streaming providers generally need to prepare several formats of the same video (termed pre-transcoding) and stream the appropriate format to the viewer. However, pre-transcoding requires enormous storage space and imposes a significant cost to the stream provider. More importantly, pre-transcoding proven to be inefficient due to the long-tail access pattern to video streams in a repository. To reduce the incurred cost, in this research, we propose a method to partially pre-transcode video streams and re-transcode the rest of it in an on-demand manner. We will develop a method to strike a trade-off between pre-transcoding and on-demand transcoding of video streams to reduce the overall cost. Experimental results show the efficiency of our approach, particularly, when a high percentage of videos are accessed frequently. In such repositories, the proposed approach reduces the incurred cost by up to 70\%.

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