Multi-cloud video distribution strategy optimization method and system

Abstract

The present invention provides a multi-cloud video distribution strategy optimization method and system, the method comprising: obtaining live video stream data within a historical period, CDN delay data of each cloud platform server, CDN distribution price and transcoding price of each transcoding template ; To clean the live video stream data, count the total number of first audience terminals in the first period of the historical period, the proportion of the minimum required bit rate and the proportion of the number of live users corresponding to each source bit rate, according to the source video bit rate and the number of audience terminals The minimum required code rate is used to classify user categories; predict the total number of second viewer terminals watching videos in the future predetermined time period, calculate the number of viewer terminals corresponding to various users in the future predetermined time period, and calculate the future Each consumption cost and each QoE value within the predetermined period; according to each consumption cost and each QoE value, determine the cloud platform server suitable for each user, and calculate the proportion of the total number of users covered by each cloud platform server within the future predetermined period.

Description

Multi-cloud video distribution strategy optimization method and system technical field [0001] The present invention relates to the field of multimedia technologies, and in particular, to a method and system for optimizing a multi-cloud video distribution strategy. Background technique [0002] For the traditional CLS (Customer Link Service, user link service), the audience can smoothly It is very important to receive video streams smoothly, and traditional live broadcast multi-cloud video distribution strategy optimization systems usually build private Some data centers and distribution networks implement transcoding and distribution operations in the live broadcast process. However, this often results in a waste of resources fee, and the cost is higher. And take advantage of the cloud platform, transfer the traditional video distribution architecture to the cloud, use CDN (Content Delivery Network, content distribution network) distribution can effectively reduce op...

AI Technical Summary

Problems solved by technology

However, the above methods are only studied from the perspective of transcoding, and have not been combined with multi-CDN distribution to form a relatively complete evaluation and decision-making system

[0005] To sum up, most of the existing technologies focus on independent research and cost optimization on the selection of CDN distribution or transcoding templates. Although the above technologies reduce distribution costs to a certain extent, the consumption price of video distribution is not only affected by transcoding The impact of the price is also affected by the distribution price, so the cost optimization method commonly used in the prior art is limited to optimize the cost

Moreover, the above-mentioned technologies do not comprehensively consider the QoE (Quality of Experience) of the audience during the cost optimization process, so it is impossible to adopt a lower-cost allocation strategy on the premise of ensuring the QoE of the audience

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