Traffic Analysis for Storage Finding in Video on Demand System

Abstract

Background and Objective: 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. Methodology: Multiple inbound and outbound connections virtually appear a single connection to the user. The session based storage finding mechanism emphasis inbounds paths from distributed storage. The minimum hop counts for storage finding effectively reduce the search cost in video on demand system. For the enhancement of overall system performance, Zipf approximation was used particularly for the outbound traffic requests from the user end. The LRFU (least recently frequently used) mechanism was implemented on the 'web cache' at storage node with a considerable cache hit ratio. The inbound traffic flows for BGP using the AS̲PATH metric to avoid loops. If the route paths are not locally organized, then the route path uses the AS̲PATH attribute to ties between the weight and local preference attributes. The attributes are used to select a particular path that controls inbound traffic. Results: This study presents novel solutions regarding the existing issues on the video traffic flow. Three stages of simulation have been observed according to the aforesaid methodology. In the first stage of simulation, traffic analysis determined the VOD system. In the second stage of simulation, it has been considered distributed database storages. In third stage number of phases considered to make complete simulations. Conclusion: Traffic control and traffic analysis methodology for video on demand system minimizes the hop count during exact storage search.