Machine Learning Technique Predicting Video Streaming Views to Reduce Cost of Cloud Services

Mahmoud Darwich

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arXiv · 2210.09078

Machine Learning Technique Predicting Video Streaming Views to Reduce Cost of Cloud Services

Mahmoud Darwich

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Abstract

Video streams tremendously occupied the highest portion of online traffic. Multiple versions of a video are created to fit the user's device specifications. In cloud storage, Keeping all versions of frequently accessed video streams in the repository for the long term imposes a significant cost paid by video streaming providers. Generally, the popularity of a video changes each period of time, which means the number of views received by a video could be dropped, thus, the video must be deleted from the repository. Therefore, in this paper, we develop a method that predicts the popularity of each video stream in the repository in the next period. On the other hand, we propose an algorithm that utilizes the predicted popularity of a video to compute the storage cost, and then it decides whether the video will be kept or deleted from the cloud repository. The experiment results show a cost reduction of the cloud services by 15% compared to keeping all video streams.

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BibTeX RIS

Mahmoud Darwich. 2022-10-17. Machine Learning Technique Predicting Video Streaming Views to Reduce Cost of Cloud Services. https://arxiv.org/abs/2210.09078

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