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随着互联网技术的快速发展以及智能设备的普及,基于HTTP的动态自适应流媒体(Dynamic Adaptive Streaming over HTTP,DASH)业务发展迅速.但在带宽受限网络中,大规模用户的视频请求,将会加重网络负载,严重影响网络带宽资源的有效利用,同时用户码率调节缺乏全局协调控制机制,容易造成网络拥塞.针对软件定义网络中的DASH视频传输业务,将视频业务提供商长期平均收益最大化作为优化目标,设计并实现了基于神经元动态规划的DASH视频路由和用户码率调节联合决策算法.最后,通过在Mininet平台上建立SDN(Software-Defined Networking)网络环境并进行对比实验,我们验证了本文提出的联合决策算法能够提高网络带宽资源利用率,最大化DASH视频业务提供商长期平均收益.
With the rapid development of Internet technology and the popularization of smart devices, the business of Dynamic Adaptive Streaming over HTTP (HTTP) -based Dynamic Adaptive Streaming over HTTP (DASH) has been rapidly developed.But in the network with limited bandwidth, large-scale users’ video requests The network load will be aggravated which will seriously affect the efficient use of network bandwidth resources and the lack of a global coordinated control mechanism for user rate adjustment will easily lead to network congestion.For the DASH video transmission service in the software defined network, the long-term average revenue of the video service provider is maximized As an optimization goal, we design and implement a joint decision algorithm of DASH video routing and user rate adjustment based on neuron dynamic programming.Finally, through the establishment of SDN (Software-Defined Networking) network environment on Mininet platform and comparative experiments, we Verify that the joint decision algorithm proposed in this paper can improve the utilization rate of network bandwidth resources and maximize the long-term average revenue of DASH video service providers.