  Applications that allow sharing of user-created short videos exploded in
popularity in recent years. A typical short video application allows a user to
swipe away the current video being watched and start watching the next video in
a video queue. Such user interface causes significant bandwidth waste if users
frequently swipe a video away before finishing watching. Solutions to reduce
bandwidth waste without impairing the Quality of Experience (QoE) are needed.
Solving the problem requires adaptively prefetching of short video chunks,
which is challenging as the download strategy needs to match unknown user
viewing behavior and network conditions. In our work, we first formulate the
problem of adaptive multi-video prefetching in short video streaming. Then, to
facilitate the integration and comparison of researchers' algorithms towards
solving the problem, we design and implement a discrete-event simulator, which
we release as open source. Finally, based on the organization of the Short
Video Streaming Grand Challenge at ACM Multimedia 2022, we analyze and
summarize the algorithms of the contestants, with the hope of promoting the
research community towards addressing this problem.
