Simulation Framework for HTTP-Based Adaptive Streaming Applications

„e popularity of Internet-based video services has signiÿcantly increased over the past years. „e de facto standard technology for Internet-based Video on Demand is HTTP-Based Adaptive Stream-ing (HAS), which is also increasingly used for live services. A core component of a HAS client is the adaptation algorithm, which dynamically adjusts the video representation to the network condi-tions. Meanwhile, there exists a large body of work on adaptation algorithms. Unfortunately, many experimental studies lack a thor-ough performance evaluation. O›en, the reason is the use of an unrealistic network environment, or incomparability of results with other studies, or a too narrow subset of evaluated parameter conÿg-urations. We argue that a simulative approach can help resolving these issues by requiring less e‡orts to set up a realistic network environment, by assisting to reproduce an experiment, and by al-lowing to parallelize simulations, and potentially run them faster than in real time. „e contribution of the present work is a design and implementation of a simulation model for a HAS-based appli-cation, including both the client and a server side. It has a clean modularized structure allowing for an easy integration of di‡erent adaptation algorithms. „e client behavior is deÿned by a Finite-State Machine that can easily be extended to include additional functionality. Moreover, the model provides extensive logging functionality for monitoring the ‰ality of Experience (QoE). We integrate three state-of-the-art algorithms into the model: FESTIVE, PANDA, and TOBASCO2. We demonstrate the usefulness of the model by running a set of experiments using a simulated indoor Wi-Fi environment.