Distributed video transcoding method and system

Abstract

The invention discloses a distributed video transcoding method and system. The method comprises the steps of obtaining source file information and target file information of a to-be-transcoded task; dividing a source video file corresponding to the to-be-transcoded task into a plurality of source video segments according to the source file information and the target file information; distributingall the source video segments to a transcoding server cluster, and transcoding the corresponding source video segments through the transcoding server cluster; and combining the target video file segments obtained by transcoding to obtain a target video file corresponding to the source video file. According to the method, the source file is divided into the plurality of source video segments according to the source file information and the target file information, and the resources are calculated for each source video segment, so that the utilization rate of cluster system resources and the transcoding efficiency of the source video files are improved.

Description

technical field [0001] The present invention relates to the technical field of transcoding, in particular to a distributed video transcoding method and system. Background technique [0002] With the development of the video industry and the popularity of mobile smart terminals, video content providers need to do a lot of video transcoding to meet the needs of a multi-terminal environment. Under the environment of the integration of three networks, one cloud and multiple screens are becoming the key layout and development direction of the video industry, so there is a huge demand for video transcoding in the fields of traditional broadcasting, Internet video websites, distance education, and video social networking. [0003] Currently, the commonly used video transcoding system has cumbersome deployment of working nodes and cannot be automatically scaled. However, in an actual application environment, the video transcoding system needs to cope with high concurrent access duri...

AI Technical Summary

Problems solved by technology

[0003] Currently, the commonly used video transcoding system has cumbersome deployment of working nodes and cannot be automatically scaled. However, in an actual application environment, the video transcoding system needs to cope with high concurrent access during certain periods of time and needs to expand cluster resources, while at other times the number of visits needs to be expanded. Small cluster resources need to be shrunk to achieve the purpose of saving cluster overhead, which causes waste of resources if deployed according to the maximum access volume, and cannot meet high-concurrency scenarios if deployed according to normal access volume

In addition, traditional audio and video transcoding systems generally use static resource allocation, and cannot allocate system resources to transcoding tasks based on their actual resource requirements when creating transcoding tasks

When the transcoding task requires a lot of computing resources, the transcoding efficiency is low; when the transcoding task requires few computing resources, the computing resources are wasted

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