Explore advanced forecasting models

Background: Chunk-based preloading in short-form video streaming aims to reduce data wastage caused by early video skips by dividing videos into smaller segments.

Question / Future Work: The authors explicitly mention that they plan to explore more advanced forecasting models to further improve system performance in predicting user viewing times, which is crucial for optimizing chunk-based preloading size.

Why It Matters: Exploring more advanced forecasting models is necessary because the study’s best-performing model, Auto-ARIMA, still produces non-trivial errors (e.g., RMSE around 6.0–8.5), and better prediction accuracy directly translates to reduced data wastage in the streaming system.

Evidence: In future work, we plan to explore more advanced forecasting models and adaptive preloading strategies to further improve system performance.