Distributed Video Quality Monitoring

Abstract

Real-time Quality of Experience monitoring be- comes an important field-of-interest for video service providers. Early detection of impairments caused by, for example, packet loss in the IP-based delivery network enables service providers to take the necessary actions in order to maximize end-users' perception of quality. The influence of network impairments on visual quality depends on characteristics of the video stream such as the amount of motion and spatial detail. Therefore, streams should be monitored and parsed beyond the network layer. In this paper, we present a distributed video stream monitoring architecture and evaluate the real-time capability of parsing video streams up to the video layer. Our results indicate that it is possible to process a single video stream up to 60Mbit/s using commodity hardware when monitoring network parameters and high level video parameters such as frame type. A higher total bitrate can be achieved when monitoring multiple video streams encoded at lower bitrates. However, when detailed video parameters such as motion vectors and residual coefficients must be gathered, specialized hardware is needed. I. INTRODUCTION In recent years video applications like video conferencing and live video streaming have gained interest and it is expected that their importance in IP networks will continue to grow. Due to the real-time character of these applications a connectionless transport protocol like UDP is typically used. Hence problems within the network can result in packet loss and late arrival of packets causing a degradation in quality of the received video stream. For video service providers it is a challenge to ensure that their service provides the minimum quality expected by the users. To ensure end-to-end quality a proactive approach is desired, by monitoring video streams at strategic demarcation points along the delivery chain, problems within the network can be detected. Measuring Quality of Experience combined with the measurement of network statistics allows operators to link quality losses to the causes at the network level. This paper describes an architecture to monitor video streams in IP networks in a distributed way. We also answer the question whether it is possible to measure network statis- tics and video application layer data for a full High Definition 1 video stream in real-time with commodity hardware. The paper is organized as follows. In section two we describe some related work in the area of video monitoring in IP networks. Section three discusses the general monitoring architecture and goes into more detail on how packets are captured and processed in the network probe. The fourth