Using predictive prefetching to improve World Wide Web latency
ACM SIGCOMM Computer Communication Review
A survey of web caching schemes for the Internet
ACM SIGCOMM Computer Communication Review
Probabilistic methods for web caching
Performance Evaluation
Cooperative Video Caching for Interactive and Scalable VoD Systems
ICN '01 Proceedings of the First International Conference on Networking-Part 2
Accelerating Internet Streaming Media Delivery using Network-Aware Partial Caching
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
GloVE: A Distributed Environment for Low Cost Scalable VoD Systems
SBAC-PAD '02 Proceedings of the 14th Symposium on Computer Architecture and High Performance Computing
Distributed prefetching scheme for random seek support in peer-to-peer streaming applications
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
A peer-to-peer network for live media streaming using a push-pull approach
Proceedings of the 13th annual ACM international conference on Multimedia
Cost-aware WWW proxy caching algorithms
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
Segmentation of multimedia streams for proxy caching
IEEE Transactions on Multimedia
IEEE Communications Magazine
Enabling adaptive video streaming in P2P systems [Peer-to-Peer Multimedia Streaming]
IEEE Communications Magazine
VMesh: Distributed Segment Storage for Peer-to-Peer Interactive Video Streaming
IEEE Journal on Selected Areas in Communications
Highly reliable inter/intra-stream FEC method for multi -server content distribution
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
A novel cache optimization algorithm and protocol for video streaming in pure peer-to-peer networks
Proceedings of the 2010 ACM workshop on Advanced video streaming techniques for peer-to-peer networks and social networking
| Hi-index | 0.00 |
In this paper, we consider a hybrid P2P video on-demand architecture that utilizes both the server and the peer resources for efficient transmission of popular videos. In our system architecture, each peer dedicates some cache space to store a particular segment of a video file as well as some of its upload bandwidth to serve the cached segment to other peers. Peers join the system and issue a streaming request to a control server. Control server directs the peers to streaming servers or to other peers who have the desired video segments. Control server also decides which peer should cache which video segment. Our main contribution in this paper is to determine the proper caching strategies at peers such that we minimize the average load on the streaming servers. To minimize the server load, we pose the caching problem as a supply-demand-based utility optimization problem. By exploiting the inherent structure of a typical on-demand streaming application as well as the availability of a global view on the current supply-demand at the control server, we demonstrate how the system performance can be significantly improved over the brute-force caching decisions. In our analysis, we mainly consider three caching mechanisms. In the first mechanism (cache prefetching), a segment is prefetched to a given peer for caching purposes upon peer's arrival to the system regardless of whether that segment is currently demanded by that peer or not. In the second mechanism (opportunistic cache update), a peer has the option of replacing the segment that is currently in its cache with the last segment that it finished streaming. In the third mechanism, we combine both mechanisms as a hybrid caching strategy. In particular, we find that a dynamic-programming (DP)-based utility maximization solution using only the cache update method performs significantly better in reducing the server load. Furthermore, our findings suggest that even less sophisticated cache update solutions can perform almost as good as prefetching strategies in interesting regions of operation.