基于知识系统的视频服务质量保障模型及仿真

Knowledge-based Video Quality Guarantee Model and Simulation

为保障Web上对实时性要求高的视频的服务质量,常通过区分服务的方法在网络边缘的节点做一些处理,但此类方法存在数据包分组标签设计不够动态,处理不够智能的问题。为此,提供了基于知识系统的视频服务质量保障模型,通过知识系统推理来获得智能,将(m,k)模型应用到标签设计中,从而提供一种有效的保障模型。仿真测试结果表明,该保障模型能够更好地满足用户的偏好需求,有效进行视频服务质量保障。

To ensure the video QoS（ quality of service） of the Web, DiffServ（ differentiated service） methods are always used at the edge of network. Current label system of DiffServ is static and not so intelligent. In order to solve this problem and improve the Subject QoS, knowledge-system-based video quality guarantee model is provided and a system is built. In this system, the video adaptation is guided intelligently with the knowledge acquired at different phases of knowledge creation processes and （m,k） model is applied in label design so as to mapping to knowledge. Testing results have shown this model can satisfy the user preference and ensure video quality effectively. So it is proved that knowledge plays an important role and brings more intelligence to our system.