TY - GEN
T1 - Incentive mechanism for proximity-based Mobile Crowd Service systems
AU - Zhang, Honggang
AU - Liu, Benyuan
AU - Susanto, Hengky
AU - Xue, Guoliang
AU - Sun, Tong
N1 - Funding Information:
This research was supported in part by NSF grants CNS-0953620, CNS-1421685, CNS-1461886, CNS-1527303, and CNS-1562264.
PY - 2016/7/27
Y1 - 2016/7/27
N2 - We investigate emerging proximity-based Mobile Crowd Service or pMCS systems, in which services are provided and consumed by users carrying smart mobile devices (e.g., smartphones) and in proximity of each other (e.g., within Bluetooth range). Due to limited resources on smartphones, it is crucial to provide a mechanism to incentivize users' participation and ensure fair trading in a pMCS system. In this paper, we design a multi-market dynamic double auction mechanism for a pMCS system, referred to as MobiAuc, and we show that it is truthful, feasible, individual-rational, no-deficit, and computationally efficient. The novelty and significance of MobiAuc is that it addresses and solves the fair trading problem in a multi-market dynamic double auction setting which naturally occurs in a mobile wireless environment. We demonstrate its efficiency via simulations based on generated user patterns (stochastic arrivals and random market clustering of users) and real-world traces. Our preliminary implementation of MobiAuc and experiments on Android platform have demonstrated the feasibility of MobiAuc mechanism in practice.
AB - We investigate emerging proximity-based Mobile Crowd Service or pMCS systems, in which services are provided and consumed by users carrying smart mobile devices (e.g., smartphones) and in proximity of each other (e.g., within Bluetooth range). Due to limited resources on smartphones, it is crucial to provide a mechanism to incentivize users' participation and ensure fair trading in a pMCS system. In this paper, we design a multi-market dynamic double auction mechanism for a pMCS system, referred to as MobiAuc, and we show that it is truthful, feasible, individual-rational, no-deficit, and computationally efficient. The novelty and significance of MobiAuc is that it addresses and solves the fair trading problem in a multi-market dynamic double auction setting which naturally occurs in a mobile wireless environment. We demonstrate its efficiency via simulations based on generated user patterns (stochastic arrivals and random market clustering of users) and real-world traces. Our preliminary implementation of MobiAuc and experiments on Android platform have demonstrated the feasibility of MobiAuc mechanism in practice.
UR - http://www.scopus.com/inward/record.url?scp=84983242566&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983242566&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2016.7524549
DO - 10.1109/INFOCOM.2016.7524549
M3 - Conference contribution
AN - SCOPUS:84983242566
T3 - Proceedings - IEEE INFOCOM
BT - IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Y2 - 10 April 2016 through 14 April 2016
ER -