``PROP: a scalable and reliable P2P assisted proxy streaming system",   

Lei Guo, Songqing Chen, Shansi Ren, Xin Chen, and Song Jiang  

Proceedings of the 24th International Conference on Distributed Computing  
Systems (ICDCS'04), Tokyo, Japan, March 23-26, 2004.  

Abstract

The demand of delivering streaming media content in the Internet has
become increasingly high for scientific, educational, and commercial
applications. Three representative technologies have been developed for
this purpose, each of which has its merits and serious limitations.
Infrastructure-based CDNs with dedicated network bandwidths and powerful
media replicas can provide high quality streaming services but at a high
cost. Server-based proxies are cost-effective but not scalable due to
the limited proxy capacity and its centralized control. Client-based P2P
networks are scalable but do not guarantee high quality streaming
service due to the transient nature of peers. To address these
limitations, we present a novel and efficient design of a scalable and
reliable media proxy system supported by P2P networks. This system is
called PROP abbreviated from our technical theme of ``collaborating and
coordinating PROxy and its P2P clients". Our objective is to address
both scalability and reliability issues of streaming media delivery in a
cost-effective way. In the PROP system, the clients' machines in an
intranet are self-organized into a structured P2P system to provide a
large media storage and to actively participate in the streaming media
delivery, where the proxy is also embedded as an important member to
ensure quality of streaming service. The coordination and collaboration
in the system are efficiently conducted by our P2P management structure
and replacement policies. We have comparatively evaluated our system by
trace-driven simulations with synthetic workloads and with a real-life
workload trace extracted from the media server logs in an enterprise
network. The results show that our design significantly improves the
quality of media streaming and the system scalability.