TY - GEN
T1 - Mobile data trading
T2 - 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
AU - Yu, Junlin
AU - Cheung, Man Hon
AU - Huang, Jianwei
AU - Poor, H. Vincent
N1 - Publisher Copyright:
© 2015 IFIP.
PY - 2015/7/6
Y1 - 2015/7/6
N2 - Motivated by the recently launched 2CM data trading platform of China Mobile Hong Kong, we study the optimal user mobile data trading problem under the future demand uncertainty. We consider a brokerage-based market, where sellers and buyers propose their selling and buying prices and quantities to the trading platform, respectively. The platform acts as a broker, which facilitates the trade by matching the supply and demand. To understand users' realistic trading behaviors, we use prospect theory (PT) from behavioral economics in the modeling, which leads to a challenging non-convex optimization problem. Nevertheless, we are able to determine the unique optimal solution in closed-form, by utilizing the unimodal structure of the objective function. When comparing with the benchmark expected utility theory (EUT), we show that a PT user with a low reference point is more willing to buy mobile data. Moreover, when the probability of high demand is low, comparing with an EUT user, a PT user is more willing to buy mobile data due to the probability distortion.
AB - Motivated by the recently launched 2CM data trading platform of China Mobile Hong Kong, we study the optimal user mobile data trading problem under the future demand uncertainty. We consider a brokerage-based market, where sellers and buyers propose their selling and buying prices and quantities to the trading platform, respectively. The platform acts as a broker, which facilitates the trade by matching the supply and demand. To understand users' realistic trading behaviors, we use prospect theory (PT) from behavioral economics in the modeling, which leads to a challenging non-convex optimization problem. Nevertheless, we are able to determine the unique optimal solution in closed-form, by utilizing the unimodal structure of the objective function. When comparing with the benchmark expected utility theory (EUT), we show that a PT user with a low reference point is more willing to buy mobile data. Moreover, when the probability of high demand is low, comparing with an EUT user, a PT user is more willing to buy mobile data due to the probability distortion.
UR - http://www.scopus.com/inward/record.url?scp=84941131371&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941131371&partnerID=8YFLogxK
U2 - 10.1109/WIOPT.2015.7151094
DO - 10.1109/WIOPT.2015.7151094
M3 - Conference contribution
AN - SCOPUS:84941131371
T3 - 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
SP - 363
EP - 370
BT - 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 May 2015 through 29 May 2015
ER -