Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Can internet video-on-demand be profitable?
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Challenges, design and analysis of a large-scale p2p-vod system
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Design and deployment of a hybrid CDN-P2P system for live video streaming: experiences with LiveSky
MM '09 Proceedings of the 17th ACM international conference on Multimedia
How P2P streaming systems scale over time under a flash crowd?
IPTPS'09 Proceedings of the 8th international conference on Peer-to-peer systems
The tube over time: characterizing popularity growth of youtube videos
Proceedings of the fourth ACM international conference on Web search and data mining
CloudMedia: When Cloud on Demand Meets Video on Demand
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Cost-Effective Partial Migration of VoD Services to Content Clouds
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Server-assisted adaptive video replication for P2P VoD
Image Communication
Flash Crowd in P2P Live Streaming Systems: Fundamental Characteristics and Design Implications
IEEE Transactions on Parallel and Distributed Systems
On the effects of caching in access aggregation networks
Proceedings of the second edition of the ICN workshop on Information-centric networking
Towards the optimal caching strategies of peer-assisted VoD systems with HD channels
ICNP '12 Proceedings of the 2012 20th IEEE International Conference on Network Protocols (ICNP)
| Hi-index | 0.00 |
Today's peer-to-peer (P2P) Video-on-Demand (VoD) systems are known to be highly scalable in a steady state. For dynamic scenarios, much effort has been spent on accommodating sharply increasing requests (known as flash crowd) with effective solutions being developed. The high popularity upon a flash crowd however does not necessarily last long, and indeed often drops very fast after the peak. Compared to growth, a decay is seemingly less challenging or even beneficial given the less user demands. While this is true in a conventional client/server system, we find that it is not the case for peer-to-peer. A quick decay can easily de-stabilize an established overlay, and the resultant smaller overlay is generally less effective for content sharing. The replication of data segments, which is critical during flash crowd, will not promptly respond to a fast and globalized population decay, either. Many of the replicas can become redundant and, even worse, their spaces cannot be utilized for an extended period. In this paper, we seek to understand the impact of such decays and the key influential factors. Based on real world trace data, we develop a mathematical model to trace the evolution of peer upload and replication during population churns, specifically during decays. Our model captures peer behaviors with common data replication and scheduling strategies in state-of-the-art peer-to-peer VoD systems. It quantitatively reveals the root causes toward escalating server load during a population decay. The model also facilitates the design of a flexible cloud based provisioning to serve highly time-varying demands.