用户密集环境下基于边缘智能的直播视频传输优化机制OACSCD

The traditional live video transmission optimization mechanism is deployed on the server side,which cannot quickly respond to the dynamic changes of the user's wireless network environment.To address this problem,a live video transmission optimization mechanism based on edge intelligence called S-Edge was proposed.It was deployed on the OpenWrt-based wireless access point,and comprehensively utilized the wireless channel state information such as airtime utilization and signal-to-noise ratio to make intelligent decisions on terminal priority and transmission rate based on fuzzy logic theory.Furthermore,the active queue management with hierarchical token bucket and service demand-driven wire-less transmission rate adaptive control technologies were introduced to realize the real-time scheduling of live video data.In order to verify the effectiveness and performance of the proposed mechanism,a high client-density environment was built through user clusters based on multi-radio interfaces in the real-world scenario.Experimental results show that S-Edge can significantly reduce the average delay and packet loss rate,which meets QoS requirements of live video transmission services in the high client-density environment.