Paper Info
Title
Incentivized Peer-Assisted Streaming for On-Demand Services
Abstract
As an efficient distribution mechanism, Peer-to-Peer (P2P) technology has become a tremendously attractive solution to offload servers in large-scale video streaming applications. However, in providing on-demand asynchronous streaming services, P2P streaming design faces two major challenges: how to schedule efficient video sharing between peers with asynchronous playback progresses? how to provide incentives for peers to contribute their resources to achieve a high level of system-wide Quality-of-Experience (QoE)? In this paper, we present iPASS, a novel mesh-based P2P VoD system, to address these challenges. Specifically, iPASS adopts a dynamic buffering-progress-based peering strategy to achieve high peer bandwidth utilization with low system maintenance cost. To provide incentives for peer uploading, iPASS employs a differentiated prefetching design that enables peers with higher contribution prefetch content at higher speed. A distributed adaptive taxation algorithm is developed to balance the system-wide QoE and service differentiations among heterogeneous peers. To assess the performance of iPASS, we built a detailed packet-level P2P VoD simulator and conducted extensive simulations. It was demonstrated that iPASS can completely offload server when the average peer upload bandwidth is more than 1.2 times the streaming rate. Furthermore, we showed that the distributed incentive algorithm motivates peers to contribute and collaboratively achieve a high level of system wide QoE.
Year
DOI
Venue
2010
10.1109/TPDS.2009.167
IEEE Trans. Parallel Distrib. Syst.
Keywords
Field
DocType
present ipass,system-wide qoe,heterogeneous peer,incentivized peer-assisted streaming,asynchronous playback,adaptive taxation algorithm,on-demand services,p2p vod system,low system maintenance cost,p2p vod simulator,high level,wide qoe,topology,bandwidth,incentive,p2p,distributed algorithms
Asynchronous communication,Peer-to-peer,Computer science,Upload,Server,Computer network,Real-time computing,Distributed algorithm,Bandwidth (signal processing),Instruction prefetch,Peering,Distributed computing
Journal
Volume
Issue
ISSN
21
9
1045-9219
Citations 
PageRank 
References 
25
0.85
22
Authors
4
Name
Order
Citations
PageRank
Chao Liang1105977.92
Zhenghua Fu257544.56
Yong Liu32402135.11
Chai Wah Wu433067.62