A New Scheme for QoE Management of Live Video Streaming in Cloud Environment

Abstract

Live video streaming process consumes very large data storage and takes very long time, so it requires big data storage and computing infrastructures for implementation. Accordingly, the use of cloud computing is becoming a common practice solution for streaming service providers. This work proposes a new scheme to manage the quality of experience (QoE) for live video streaming viewers, aimed directly at cloud computing environments. This scheme proposes to make optimal usage of cloud computing resources and quality services to meet the quality of experience (QoE) requirements of the live video streaming viewers without considering another cost to the video service provider. We examine the user’s quality of experience using dynamic adaptive streaming HTTP (DASH) technique. Then, we present and derive three important performance indicators which effect on viewer’s QoE namely: startup delay, deadline time (time nulling including null duration and number of null time), and bit rate level variations. The simulation results show that the tested indication parameters do not need to access the service providers in order to manage QoE of viewers neither do not need to insert them into the video streaming client software to determine the user experience in live video streaming. So, we believe that our proposed scheme and the performance indicators that studied in our work can serve as useful and light-weight tools for live video streaming service provider to monitor and control their quality of services.