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A resource prediction method for multi-version video-on-demand streaming media server clusters

A streaming media server and video-on-demand technology, applied in image communication, selective content distribution, electrical components, etc., can solve the problem of not considering the highly dynamic and dynamic changes of VOD application load, improve cluster resource utilization, guarantee The effect of user experience

Active Publication Date: 2018-07-06
XI AN JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] None of the above-mentioned related invention patents considers the highly dynamic nature of the VOD application load and the random arrival of user requests, resulting in the dynamic changes in the required server cluster resources, thus creating a multi-version video-on-demand streaming media server cluster resource prediction method to improve user to experience

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  • A resource prediction method for multi-version video-on-demand streaming media server clusters
  • A resource prediction method for multi-version video-on-demand streaming media server clusters
  • A resource prediction method for multi-version video-on-demand streaming media server clusters

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Embodiment Construction

[0041] The implementation of the present invention will be described in detail below in conjunction with the drawings and examples.

[0042] as attached figure 1 As shown, the present invention is a multi-version video-on-demand streaming media server cluster resource prediction method, by analyzing user historical video-on-demand behavior logs, mining user video-on-demand behavior characteristics and rules, and establishing user video-on-demand behavior models; according to user video-on-demand behavior The model uses queuing theory to build a resource prediction model for streaming media server clusters in multi-version video on demand, and calculates the amount of resources required by streaming media server clusters, so as to achieve the purpose of ensuring user experience and improving cluster resource utilization.

[0043] The technical solution of the present invention will be described in detail below.

[0044] 1. The arrival rate of user video-on-demand requests

[00...

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Abstract

The present invention is a multi-version video-on-demand stream media server cluster resource prediction method. By analyzing user historical video-on-demand behavior logs, mining user video-on-demand behavior characteristics and rules, and establishing a user video-on-demand behavior model; according to the user video-on-demand behavior model, using The queuing theory constructs a resource prediction model for streaming media server clusters in multi-version video-on-demand, and calculates the amount of resources required by streaming media server clusters, so as to achieve the purpose of ensuring user experience and improving cluster resource utilization.

Description

technical field [0001] The invention belongs to the technical field of video-on-demand, relates to video-on-demand, streaming media servers, and resource prediction, and in particular to a multi-version video-on-demand streaming server cluster resource prediction method. Background technique [0002] With the rapid development of WIFI, 3G, 4G and even LTE wireless communication technologies and various mobile smart terminals, users can access multimedia video resources anytime and anywhere on various mobile devices. In order to cope with the diversity of mobile terminal types and heterogeneous networks Access methods, multi-version video on demand came into being. The current research on multi-version video on demand mainly includes: 1) scalable video coding technology; 2) real-time video transcoding; 3) multi-version video storage. However, storing all versions in advance requires huge storage resources, and the unpredictability of the versions makes it unrealistic to prep...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N21/442H04L29/08
CPCH04L67/1004H04N21/44204H04N21/44213
Inventor 郑庆华赵辉李珍艳朱子豪熊双双张未展
Owner XI AN JIAOTONG UNIV