Toward an Adaptive Screencast Platform: Measurement and Optimization

Abstract

The binding between computing devices and displays is becoming dynamic and adaptive, and screencast technologies enable such binding over wireless networks. In this article, we design and conduct the first detailed measurement study on the performance of the state-of-the-art screencast technologies. Several commercial and one open-source screencast technologies are considered in our detailed analysis, which leads to several insights: (1) there is no single winning screencast technology, indicating room to further enhance the screencast technologies; (2) hardware video encoders significantly reduce the CPU usage at the expense of slightly higher GPU usage and end-to-end delay, and should be adopted in future screencast technologies; (3) comprehensive error resilience tools are needed as wireless communication is vulnerable to packet loss; (4) emerging video codecs designed for screen contents lead to a better Quality of Experience (QoE) of screencast; and (5) rate adaptation mechanisms are critical to avoiding degraded QoE due to network dynamics. As a case study, we propose a nonintrusive yet accurate available bandwidth estimation mechanism. Real experiments demonstrate the practicality and efficiency of our proposed solution. Our measurement methodology, open-source screencast platform, and case study allow researchers and developers to quantitatively evaluate other design considerations, which will lead to optimized screencast technologies.