In an on-demand video system, the repository servers storing all the video contents generally have limited streaming capacities and may not be co-located with the users. To achieve higher user capacity and lower network transmission cost, distributed servers architecture can be used. In such a system, multiple local servers are placed close to the user pools and, according to their local demands, the servers dynamically cache the contents streamed from the repository. We study in this paper a number of caching schemes by considering whether the local servers can exchange their cached contents among themselves or not. All the caching schemes keep a sliding window worth of data for each video being displayed; hence a video can be partially stored. We study the trade-off between the storage capacity required and the network channel used in each scheme, and address how the system cost can be minimized by appropriately sizing the window. We also show the cost advantage in using such a syste...

A hierarchical storage system achieves scalable storage in providing on-demand video services. In such a system, video files are stored in a tertiary level (such as a library or jukebox), and transferred to a secondary level (such as magnetic disks) from which it is streamed to the users. In this paper, we study the design of such a system for interactive applications in which a movie has to be completely transferred (or "staged") to the secondary level before it is displayed to its user; thereby incurring some user delay. We specify the required storage and bandwidth to meet a delay goal, given application characteristics. We have developed an accurate and yet simple model for the system, which greatly facilitates the design process and allows us to extract important performance characteristics of the system. We provide some design examples, and study the influence of video popularity. Keywords---Hierarchical storage systems, interactive video services, tertiary storage, secondary st...

In near video-on-demand, requests for the same movie arriving within a period of time are grouped together (i.e., batched) and served with a single multicast stream; thereby reducing the bandwidth requirement compared with the unbatched case. We consider here that the use of a multicast channel comes with a cost. Since delayed users may cancel their requests while being batched, this uncollected revenue has to be appropriately balanced with the channel usage cost in order to achieve maximum profit. We address here profit issues for a number of batching schemes. In the window-based schemes, users are batched for a fixed period of time before they are served; in the batch-size based scheme, users are served once a certain number of them are collected. We study the system profit in terms of user reneging behavior, movie popularity, and multicast channel cost. By combining the advantages of the window-based and the batchsize based schemes, we introduce a scheme which adapts to the fluctuat...

An increasingly common feature of a Set Top Box (STB) is that of a Personal/Digital Video Recorder (PVR), which enables subscribers to record broadcasted content to be viewed at a later time – time-shifting. Currently, subscribers have the limited choice of watching time-shifted shows either from their own PVRs or from a centralized VoD server that makes available only the popular shows for time shifted viewing. Our CommunityPVR—a new system that forms a peer-to-peer network among the STBs and streams recorded content among peer STBs—makes available less popular titles to niche audiences (the long tail effect) of a community without incurring addtional cost to service providers for servers, bandwidth, and storage. In this paper, we present an analytical model to investigate how far along the tail of the popularity curve can be covered by CommunityPVR. Using TV shows ranked by Nielsen Media Research and VoD shows from China Telecom, our model provides a framework to determine the number of copies of broadcast/VoD content recorded by a community and the probability that CommunityPVR is able to deliver an on-demand stream of a given show over a DSL network. For example, CommunityPVR can stream near DVD quality video of the top ranked 5000 shows with 100 % probability to a community of 100K. Unlike a centralized VoD solution, CommunityPVR has the potential to deliver both popular and long tail content on demand to a service provider’s community in a cost-effective manner. 1.