TY - GEN
T1 - Peer-to-peer video on demand
T2 - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
AU - Pai, Vijay S.
AU - Yung, Ryn Choe
AU - Dyaberi, Jagadeesh
AU - Schuff, Derek
AU - Kannan, Karthik
PY - 2009
Y1 - 2009
N2 - The challenges and solutions required for peer-to-peer video-on-demand (P2P VoD) provided by a fixed provider such as a cable company are fundamentally different from those seen in traditional P2P networks or client-server VoD solutions. Unlike traditional P2P networks, the end nodes (set top boxes with DVR capabilities) are largely under control of the system provider. Consequently, issues like churn and free-loading are less substantial. Unlike client-server solutions, there is always a readily-available resource of peer nodes able to contribute even if they are not using the VoD service! This paper explores requirements for efficient preloading of VoD movie data onto numerous customer set-top boxes. This research is currently exploring mathematical programming algorithms that minimize uplink traffic, given a popularity model for various pieces of content and information about storage and bandwidth capacity constraints at the customer nodes. Given the complex non-linear nature of P2P interactions, these mathematical programs require non-linear optimization approaches or heuristic solutions. However, even heuristic solutions would likely provide substantial advantages over simple dynamic allocation.
AB - The challenges and solutions required for peer-to-peer video-on-demand (P2P VoD) provided by a fixed provider such as a cable company are fundamentally different from those seen in traditional P2P networks or client-server VoD solutions. Unlike traditional P2P networks, the end nodes (set top boxes with DVR capabilities) are largely under control of the system provider. Consequently, issues like churn and free-loading are less substantial. Unlike client-server solutions, there is always a readily-available resource of peer nodes able to contribute even if they are not using the VoD service! This paper explores requirements for efficient preloading of VoD movie data onto numerous customer set-top boxes. This research is currently exploring mathematical programming algorithms that minimize uplink traffic, given a popularity model for various pieces of content and information about storage and bandwidth capacity constraints at the customer nodes. Given the complex non-linear nature of P2P interactions, these mathematical programs require non-linear optimization approaches or heuristic solutions. However, even heuristic solutions would likely provide substantial advantages over simple dynamic allocation.
KW - Mathematical programming
KW - Video-on-demand
UR - https://www.scopus.com/pages/publications/70449567649
UR - https://www.scopus.com/pages/publications/70449567649#tab=citedBy
U2 - 10.1109/ICME.2009.5202799
DO - 10.1109/ICME.2009.5202799
M3 - Conference contribution
AN - SCOPUS:70449567649
SN - 9781424442911
T3 - Proceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
SP - 1544
EP - 1545
BT - Proceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
Y2 - 28 June 2009 through 3 July 2009
ER -