Calibration and Prediction of Streaming-Server Performance

Overview

Streaming media is gaining in popularity for viewing both, video-on-demand content as well as live Webcasts. Streaming servers must meet strict data-delivery timing constraints in order to provide acceptable viewing quality. These constraints can be achieved only if the servers are not allowed to exceed their operational saturation point. At the same time, providers of streaming services need to maximize the use of their infrastructure to remain cost-effective. These competing goals motivate development of detailed models that predict server saturation points under extremely diverse workloads. This paper proposes a methodology that can build predictive models using a relatively small number of calibration workloads.