Traffic Analysis for Storage Finding in Video on Demand System

TL;DR

This paper emphasizes the importance of traffic analysis and control in Video on Demand systems to optimize storage retrieval and reduce latency in large-scale distributed storage architectures.

Contribution

It introduces a methodology for traffic analysis and control to improve storage finding efficiency in VOD systems.

Findings

Traffic growth in IP-based video is over 30% annually.

Mobile network video traffic growth exceeds 80%.

Traffic control reduces hop count for media retrieval.

Abstract

The literature survey typically predicated sharp growth for IP-based video traffic i.e., 30% or more annually. For the Internet TV in mobile networks, video traffic growth rate is expected to rise 80% or more. These high growth rates of video traffic will account for a large portion of the bandwidth. The performance of video-on-demand system during real-time data streaming greatly depends on the session oriented data-storage finding in the mass scale distributed storage architecture. At the storage end, data is broken up into manageable chunks of data packets, which could be smoothly, deliver over the Internet. The objective of this study was to present the necessity of traffic control and traffic analysis methodology in the video on demand system to minimize the hop count for finding exact media storage to retrieve video chunk data.