A payment-based incentive and service differentiation scheme for peer-to-peer streaming broadcast

Guang Tan*, Stephen A. Jarvis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)


We propose a novel payment-based incentive scheme for peer-to-peer (P2P) live media streaming. Using this approach, peers earn points by forwarding data to others. The data streaming is divided into fixed length periods; during each of these periods peers compete with each other for good parents (data suppliers) for the next period in a first-price-auction-like procedure using their points. We design a distributed algorithm to regulate peer competitions, and consider various individual strategies for parent selection from a game theoretic perspective. We then discuss possible strategies that can be used to maximize a peer's expected media quality by planning different bids for its substreams. Finally, in order to encourage off-session users to remain staying online and continue contributing to the network, we develop an optimal data forwarding strategy that allows peers to accumulate points that can be used in future services. Simulations results show that proposed methods effectively differentiate the media qualities received by peers making different contributions (which originate from, for example, different forwarding bandwidths or servicing times), and at the same time maintaining a high overall system performance.

Original languageEnglish
Pages (from-to)940-953
Number of pages14
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number7
Publication statusPublished - 2008

Bibliographical note

Funding Information:
The authors are grateful to the anonymous reviewers for their excellent feedback. This work was funded in part by the Engineering and Physical Sciences Research Council (EPSRC) under grant EP/F000936/1.


  • Incentive
  • Media streaming
  • Payment
  • Peer-to-peer
  • Service differentiation

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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