SVC video transmission method based on intelligent edge and intelligent edge

Abstract

The invention discloses an SVC video transmission method based on an intelligent edge and the intelligent edge, and the method comprises the steps: determining the video priority corresponding to a video block when the intelligent edge receives a video block downloading request; enabling the intelligent edge to acquire network state information of a network where the video block downloading request is located; enabling the intelligent edge to determine a video layer number corresponding to the video block according to the network state information and the video priority, and acquiring a videolayer corresponding to the video block from a server according to the video layer number; and enabling the intelligent edge to issue the acquired video layer to each user side in a user cluster corresponding to the video block. In this way, the intelligent edge is assembled on the network edge of the network, and the intelligent edge issues different numbers of SVC video layers to each user side by using the network state information and the video priority to provide video streams with different qualities for different users, so the QoE joint optimization of SVC video users is realized, and the income of a content provider is improved.

Description

technical field [0001] The present application relates to the field of live broadcast technology, and in particular to an intelligent edge-based SVC video transmission method and an intelligent edge. Background technique [0002] With the gradual maturity and promotion of 4G / 5G technology, the improvement of playback equipment and the emergence of live video applications, the live broadcast industry has been booming in recent years, and live video traffic accounts for an increasing proportion of network traffic. According to Cisco's 2018 Network Traffic Forecast Report, live video traffic will increase 15-fold from 2017 to 2022. With the continuous growth of live video traffic, it is of great significance to achieve joint optimization of user quality of experience (QoE). However, the user QoE will be affected by the network environment, for example, the complex and changeable network environment will lead to poor QoE and so on. [0003] In order to solve the problem of poo...

AI Technical Summary

Problems solved by technology

However, since multiple users in the same area often request live video streams at the same time in the network, multiple users often compete for the same shared bottleneck bandwidth resources at the access points of social networks and campus networks, resulting in poor user QoE. Stable, the performance of user QoE joint optimization is not good, and the revenue of content providers is reduced

Images