Single Video Performance Analysis for Video-on-Demand Systems
This work addresses cache efficiency for video-on-demand providers, but it is incremental as it builds on existing analysis methods.
The paper tackles the content placement problem in video-on-demand systems by reducing multi-video analysis to decoupled single-video systems, proposing a hybrid placement technique that achieves near-optimal performance with low complexity.
We study the content placement problem for cache delivery video-on-demand systems under static random network topologies with fixed heavy-tailed video demand. The performance measure is the amount of server load; we wish to minimize the total download rate for all users from the server and maximize the rate from caches. Our approach reduces the analysis for multiple videos to consideration of decoupled systems with a single video each. For each placement policy, insights gained from the single video analysis carry back to the original multiple video content placement problem. Finally, we propose a hybrid placement technique that achieves near optimal performance with low complexity.