Cost-Efficient Storage for On-Demand Video Streaming on Cloud
Mahmoud Darwich, Yasser Ismail, Talal Darwich, Magdy Bayoumi

TL;DR
This paper proposes a hierarchical cloud storage method for video streams that reduces storage costs by up to 40% by selectively pre-transcoding videos based on access frequency.
Contribution
It introduces a novel cost-minimization approach for storing and transcoding videos in hierarchical cloud storage, optimizing resource use and reducing expenses.
Findings
Cost reduction of up to 40% in storage for frequently accessed videos
Effective hierarchical storage decision strategy demonstrated through simulations
Significant savings in cloud storage costs for on-demand video streaming
Abstract
Video stream is converted to several formats to support the user's device, this conversion process is called video transcoding, which imposes high storage and powerful resources. With emerging of cloud technology, video stream companies adopted to process video on the cloud. Generally, many formats of the same video are made (pre-transcoded) and streamed to the adequate user's device. However, pre-transcoding demands huge storage space and incurs a high-cost to the video stream companies. More importantly, the pre-transcoding of video streams could be hierarchy carried out through different storage types in the cloud. To minimize the storage cost, in this paper, we propose a method to store video streams in the hierarchical storage of the cloud. Particularly, we develop a method to decide which video stream should be pre-transcoded in its suitable cloud storage to minimize the overall…
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