Research On Wireless Multi-view Video Service Quality Control Mechanism

Multi-view video refers to placing multiple cameras in the scene,recording multiple view data,and providing the user with the interactive ability of view selection and scene roaming.Compared with traditional single-view 2D video,multi-view video matches people's visual needs more closely.It can provide a rich sense of three-dimensionality and immersion,and can freely switch viewing angles according to user needs,while also requiring more transmission resources.However,the service resources of the live video platform,including its transcoding resources and video stream distribution resources are limited,and the cost is very high.Therefore,in the face of a large number of videos,how to reasonably allocate service resources has become an urgent problem to be solved by the video live broadcast platform.Because viewers cannot receive video representations that exceed their own bandwidth capacity,the QoE(Quality of Experience)adopted in this paper is based on the received video representations and the viewer's available bandwidth to determine overall satisfaction.The total user satisfaction achieved by using a specific set of video resolutions is regarded as a profit or gain,while the number of cloud instances consumed and the total bandwidth of all users are used as weights respectively.The resource allocation problem is converted to a mixed integer-based multi-constraint planning and multi-choice knapsack strategy to find the best resource allocation of the video representation set,and the CPLEX optimizer are used to find the optimal solution.In this paper,based on the fair representation selection algorithm,one of the classical algorithms,the algorithm is improved by analyzing the packet loss in the video transmission process and the influence of the distance between the user and the base station.The specific ways to improve as follows:(1)The different signal-to-noise ratio of the wireless channel are not considered in the original method,and the data packet will have different packet loss rates during channel transmission.This paper compensates the video bandwidth resources in transmission according to the actual channel packet loss rate.This method can ensure that even if part of the data is lost during transmission,the resolution of the video image can still reach the expected value.(2)In the original method,the influence of the distance between the user and the base station on the channel capacity was not fully considered.This article refers to the distance between the user and the base station and assigns different bit rates to users with different distances.The specific method is to divide users into inner circle,middle circle and outer circle users according to the distance.If the user is in the middle circle or the middle circle,the video quality sented by the server is adjusted according to the actual limit of the bandwidth that can be received to improve the resource utilization.This paper uses the resume optimization model to solve the optimization problem.Finally,the improved algorithm is used as the experimental group,the best representation selection(QoE generated by the CPLEX optimizer)and the FBRS strategy are used as the control group,the experimental performance was compared from different performance indicators The experiments show that the algorithm in this paper is higher than the comparison algorithm.