Research On Multi-channel Live Video System Based On P2P In Hybrid Cloud Environment

In recent years,with the progress of Internet and streaming media technology,the video broadcast has gained a large-scale popularity.Researchers at home and abroad have conducted research on live broadcast applications and have improved the service performance of live broadcast systems gradually.However,the current video broadcast system can't provide good service to users in terms of large-scale users.Traditional video broadcast system deployed a large number of video servers to provide services,which increasing system costs and limiting the development of video broadcast technology.Moreover,due to the particularity of video broadcast on video quality and the frequent switching of channels in a multi-channel live broadcast system,requiring the system with higher requirements.The current video broadcast mechanism needs to be further improved.The development and application of cloud storage technology makes it possible to build a live system with large cost to meet the requirements of large-scale user.Through the study of cloud storage technology,this paper focuses on cloud storage technology and the advantages of using hybrid cloud storage to design a live broadcast system.The cloud storage technology has the advantages of lower cost and good flexibility to improve the system.Based on the analysis of the current popular P2 P technology and the advantage of P2 P technology,a multi-channel video live broadcast system(MSHP,The system of multi-channel live streaming based on hybrid cloud storage and P2P)is designed.MSHP designed the system architecture of multi-channel live broadcast system in detail,and analyzed the distribution of video resources quantitatively.The main tasks of MSHP are as follows:Designed the system architecture of multi-channel live broadcast system.The stable public cloud server is adopted as video servers,and the service performance and scalability of the system is increased by adopting the edge node with lower cost and better service performance.Designed the system video data distribution strategy.Distributing the corresponding video stream according to the user request information,balances the system load,and fully utilizes the upload bandwidth of the edge node.Adjusting the video streaming distribution strategy dynamically.Monitoring user request status timely,and adjusting the live streaming video streaming distribution strategy dynamically according to the set value of the cycle and through the statistics of user request information.Establishing a live broadcast system to adjust the video streaming distribution strategy model and optimizing the transmission efficiency of the system.The length of live broadcast system adjusting is related to the calculation frequency of the video server and the response time to the user request.In this paper,a dynamic adjustment mechanism of period value is established to maximize the transmission efficiency of the system.