TY - GEN
T1 - Incentivizing sharing in realtime D2D streaming networks
T2 - 34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
AU - Li, Jian
AU - Bhattacharyya, Rajarshi
AU - Paul, Suman
AU - Shakkottai, Srinivas
AU - Subramanian, Vijay
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/21
Y1 - 2015/8/21
N2 - We consider the problem of streaming live content to a cluster of co-located wireless devices that have both an expensive unicast base-station-to-device (B2D) interface, as well as an inexpensive broadcast device-to-device (D2D) interface, which can be used simultaneously. Our setting is a streaming system that uses a block-by-block random linear coding approach to achieve a target percentage of on-time deliveries with minimal B2D usage. Our goal is to design an incentive framework that would promote such cooperation across devices, while ensuring good quality of service. Based on ideas drawn from truth-telling auctions, we design a mechanism that achieves this goal via appropriate transfers (monetary payments or rebates) in a setting with a large number of devices, and with peer arrivals and departures. Here, we show that a Mean Field Game can be used to accurately approximate our system. Furthermore, the complexity of calculating the best responses under this regime is low. We implement the proposed system on an Android testbed, and illustrate its efficient performance using real world experiments.
AB - We consider the problem of streaming live content to a cluster of co-located wireless devices that have both an expensive unicast base-station-to-device (B2D) interface, as well as an inexpensive broadcast device-to-device (D2D) interface, which can be used simultaneously. Our setting is a streaming system that uses a block-by-block random linear coding approach to achieve a target percentage of on-time deliveries with minimal B2D usage. Our goal is to design an incentive framework that would promote such cooperation across devices, while ensuring good quality of service. Based on ideas drawn from truth-telling auctions, we design a mechanism that achieves this goal via appropriate transfers (monetary payments or rebates) in a setting with a large number of devices, and with peer arrivals and departures. Here, we show that a Mean Field Game can be used to accurately approximate our system. Furthermore, the complexity of calculating the best responses under this regime is low. We implement the proposed system on an Android testbed, and illustrate its efficient performance using real world experiments.
UR - https://www.scopus.com/pages/publications/84954202507
U2 - 10.1109/INFOCOM.2015.7218597
DO - 10.1109/INFOCOM.2015.7218597
M3 - Conference contribution
AN - SCOPUS:84954202507
T3 - Proceedings - IEEE INFOCOM
SP - 2119
EP - 2127
BT - 2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 April 2015 through 1 May 2015
ER -