Stream media VoD system for intelligent access data

Abstract

The utility model relates to a streaming media on-demand system with intelligent data access which can reduce manual interference as possible, improve the efficiency of system and reinforce intellectualization of system, which comprises a media operational environmental module, an additive information module, an intelligent storage strategy module, a breakpoint continuous transmitting-file module, a breakpoint loading-media module, a periodical deleting-file module, a data analysis and recovery module, a system recovery module and a foreground on-demand system. The utility model actively performs background data generation and controls automatic storage, continuous file transmission and various malfunction analysis of media file, and then according to the analysis result, the intelligent recovery of the system is made, thereby reducing manual interference as possible, improving the efficiency of system, and reinforcing the intellectualization of system. The utility model has the advantages that manual intelligent decision-making support system and the design integrating with the technique of concentrative database system enable the intellectualization and safety performance of the system is more outstanding.

Description

Technical field: [0001] The invention relates to a streaming media on-demand system. Background technique: [0002] With the popularization and development of streaming media technology, video-on-demand has changed from stand-alone on-demand to network-based on-demand. The video on demand system (VOD) undergoes a qualitative change. People can make full use of the huge storage space of the Internet to share a large number of video resources. With the application of streaming media technology, it is not difficult to find that the current media video-on-demand system has greatly improved the efficiency of video-on-demand in essence. But there are still many problems that need to be solved urgently. One of them is several problems in access (including file access on the media server and background data access on the on-demand server). One is that the file access on the media server is relatively concentrated and unbalanced, and load balancing is rarely achieved ; Every time...

AI Technical Summary

Problems solved by technology

All of these need to be manually searched, and the implementation is rather cumbersome; secondly, generally speaking, the media file is uploaded through the background web page or the copy command after locating the target storage location of the media server. When uploading the media file, if power failure, In unexpected situations such as disconnection, media files can only be re-uploaded, especially when encountering large files, it will take too much time, resulting in low work efficiency; Infection and destruction of various factors make the files unable to be played on demand; when there are relatively many media files on the server, it is not easy to find those damaged files; Fourth, when the system as a whole crashes, the server needs to relocate the storage It takes a lot of time and energy to complete the media files and reconstruct the background database information of the on-demand system

A lot of practice has proved that in order to achieve load balancing in a distributed video-on-demand system, there are two main problems: one is how to store video files; the other is how to schedule servers that respond to on-demand requests

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