TY - JOUR
T1 - Auction-based on-demand P2P min-cost media streaming with network coding
AU - Chu, Xiaowen
AU - Zhao, Kaiyong
AU - Li, Zongpeng
AU - Mahanti, Anirban
N1 - Funding Information:
The research of Chu and Zhao is partially supported by the Hong Kong RGC under Grant HKBU, 210406E, and FRG grant HKBU FRG/07-08/II-36.
PY - 2009/12
Y1 - 2009/12
N2 - Realizing on-demand media streaming in a Peer-to-Peer (P2P) fashion is more challenging than in the case of live media streaming, since only peers with close-by media play progresses may help each other in obtaining the media content. The situation is further complicated if we wish to pursue low aggregated link cost in the transmission. In this paper, we present a new algorithmic perspective toward on-demand P2P streaming protocol design. While previous approaches employ streaming trees or passive neighbor reconciliation for media content distribution, we instead coordinate the streaming session as an auction where each peer participates locally by bidding for and selling media flows encoded with network coding. We show that this auction approach is promising in achieving low-cost on-demand streaming in a scalable fashion. It is amenable to asynchronous, distributed, and lightweight implementations, and is flexible to provide support for random-seek and pause functionalities. Through extensive simulation studies, we verify the effectiveness and performance of the proposed auction approach, focusing on the optimality in overall streaming cost, the convergence speed, and the communication overhead.
AB - Realizing on-demand media streaming in a Peer-to-Peer (P2P) fashion is more challenging than in the case of live media streaming, since only peers with close-by media play progresses may help each other in obtaining the media content. The situation is further complicated if we wish to pursue low aggregated link cost in the transmission. In this paper, we present a new algorithmic perspective toward on-demand P2P streaming protocol design. While previous approaches employ streaming trees or passive neighbor reconciliation for media content distribution, we instead coordinate the streaming session as an auction where each peer participates locally by bidding for and selling media flows encoded with network coding. We show that this auction approach is promising in achieving low-cost on-demand streaming in a scalable fashion. It is amenable to asynchronous, distributed, and lightweight implementations, and is flexible to provide support for random-seek and pause functionalities. Through extensive simulation studies, we verify the effectiveness and performance of the proposed auction approach, focusing on the optimality in overall streaming cost, the convergence speed, and the communication overhead.
KW - Auction algorithms.
KW - Communication/networking and information technology
KW - Computer systems organization. multicast
KW - Design studies
KW - Internet working
KW - Media streaming
KW - Overlay networks
KW - Performance of systems
UR - http://www.scopus.com/inward/record.url?scp=74449083975&partnerID=8YFLogxK
U2 - 10.1109/TPDS.2009.40
DO - 10.1109/TPDS.2009.40
M3 - Journal article
AN - SCOPUS:74449083975
SN - 1045-9219
VL - 20
SP - 1816
EP - 1829
JO - IEEE Transactions on Parallel and Distributed Systems
JF - IEEE Transactions on Parallel and Distributed Systems
IS - 12
M1 - 4798159
ER -