MMApr 22, 2021

Improving Hierarchy Storage for Video Streaming in Cloud

arXiv:2104.11317v19 citations
Originality Synthesis-oriented
AI Analysis

This work addresses storage cost optimization for video streaming companies using cloud services, representing an incremental improvement.

The paper tackles the high cost of storing multiple video stream formats in cloud storage by proposing a method to manage cloud hierarchy storage, resulting in a cost reduction of 18.75%.

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 %.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes