Improving Hierarchy Storage for Video Streaming in Cloud

TL;DR

This paper presents a hierarchical cloud storage management method for video streaming that optimizes storage costs by dynamically storing video parts in suitable cloud types, achieving significant cost reduction.

Contribution

It introduces a novel algorithm for managing hierarchical cloud storage tailored for frequently accessed video segments, improving cost efficiency.

Findings

Achieved an 18.75% reduction in cloud storage costs.

Effectively manages storage based on access patterns.

Demonstrated promising experimental results.

Abstract

Frequently accessed video streams are pre-transcoded into several formats to satisfy the characteristics of all display devices. Storing several video stream formats imposes a high cost on video stream providers using the old classical way. Alternatively, cloud providers offer a high flexibility of using their services and at a low cost relatively. Therefore, video stream companies adopted cloud technology to store their video streams. Generally, having all video streams stored in one type of cloud storage, the cost rises gradually. More importantly, the variation of the access pattern to frequently accessed video streams impacts negatively the storage cost and increases it significantly. To optimize storage usage and lower its cost, we propose a method that manages the cloud hierarchy storage. Particularly, we develop an algorithm that operates on parts of different videos that are frequently accessed and stores them in their suitable storage type cloud. Experiments came up with promising results on reducing the cost of using cloud storage by 18.75 %.