QoE-driven HAS live broadcast channel scheduling method in cloud computing environment

Abstract

The invention discloses a QoE-driven HAS live broadcast channel scheduling method in a cloud computing environment. The method comprises a calculation method and a model of an average user QoE. Basedon the calculation method or the model of the average user QoE, the HAS live broadcast channel can be initialized, deployed and dynamically scheduled. In the scenario of cloud resource initializationallocation, the HAS live broadcast channel initialization deployment method is studied to optimize the QoE of users under the given cloud resource supply state, so as to maximize the QoE of average users under the condition of satisfying the maximum resource limit of each virtual streaming media server. Aiming at the scenario of cloud resource dynamic integration, a dynamic scheduling method of HAS live broadcast channel is studied to optimize the QoE of the users to be on-line, so that the QoE of the average users can be maximized even under the limited cloud resource supply.

Description

technical field [0001] The invention belongs to the field of multimedia live broadcast, and in particular relates to a QoE-driven HAS live channel scheduling method in a cloud computing environment. Background technique [0002] With the rapid development of Internet and multimedia technology, HTTP Adaptive Streaming (HAS) service has become the mainstream trend of streaming media content distribution under heterogeneous network and terminal environment. With the market scale of the cloud computing industry, large-scale streaming media services in the cloud computing environment are increasingly favored by users. How to deploy HAS services on the cloud computing platform while ensuring the quality of experience (QoE) of users has important research significance. [0003] The retrieved following patents related to the present invention and belonging to the field of QoE-driven HAS streaming media services are: [0004] 1. Chinese patent 201610846542.X, a QoE-driven multi-cha...

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Problems solved by technology

[0010] None of the above-mentioned related invention patents takes into account the adaptive live broadcast of streaming media based on the cloud computing environment, and cannot consider the global optimization of resources in the cloud computing environment in large-scale and dynamic streaming media adaptive live broadcast scenarios. The optimal allocation of resources is closely combined with the service quality evaluation method, so it is necessary to develop a QoE-driven HAS live channel scheduling method in the cloud computing environment to optimize the average user's QoE

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