``Design and evaluation of a scalable and reliable P2P assisted proxy for 
on-demand streaming media delivery" 
 
Lei Guo, Songqing Chen, and Xiaodong Zhang

IEEE Transactions on Knowledge and Data Engineering, Vol. 18, No. 5, 2006, 
pp. 669-682. 

Abstract

To efficiently deliver streaming media, researchers have developed technical 
solutions that fall into three categories, each of which its merits and 
limitations. Infrastructure-based CDNs with dedicated network bandwidths and 
hardware supports 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 in storage and bandwidth, and its centralized control 
also brings a single point of failure. Client-based P2P networks are 
scalable, bit 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 assisted 
by P2P networks, called PROP. 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 embeded as an important member to ensure the quality 
of streaming service. The coordination and collaboration in the system are 
efficiently conducted by our P2P management structure and replacement policies.
Our system has the following merits: 1) It addresses both the scalability 
problem in centralized proxy systems and the unreliable service concern by 
only relying on the P2P sharing of clients. 2) The proposed content locating 
scheme can timely serve the demanded media data and fairly dispatch media 
streaming tasks in appropriate granularity across the system. 3) Based on the 
modeling and analyis, we propose a global replacement policies for proxy 
and clients, which well balance the demand and supply of streaming data in the
system, achieving a high utilization of peers' cache. We have comparatively
evaluated our system through trace-driven simulations with synthetic workloads 
and with a real-life workload extracted from the media server logs in 
an enterprise network, which shows our design significantly improves the 
quality of media streaming and the system scalability.