TY - GEN
T1 - Cooperative Wi-Fi deployment
T2 - 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
AU - Yu, Haoran
AU - Cheung, Man Hon
AU - Huang, Jianwei
N1 - Publisher Copyright:
© 2015 IFIP.
PY - 2015/7/6
Y1 - 2015/7/6
N2 - In this paper, we study the cooperative Wi-Fi deployment problem, where the mobile network operator (MNO) cooperates with some venue owners (VOs) to deploy public Wi-Fi networks. The MNO negotiates with the VOs to determine where to deploy Wi-Fi and how much to pay. The MNO's objective is to maximize its payoff, which depends on the payments to VOs, the benefits due to data offloading and mobile advertising, and the costs due to deploying and operating Wi-Fi. We analyze the interactions among the MNO and VOs under the one-to-many bargaining framework, where the MNO bargains with VOs sequentially, taking into account the externalities among different steps of bargaining. We apply the Nash bargaining theory to analyze the cases with exogenous and endogenous bargaining sequences. For the former case, the bargaining sequence is predetermined, and we apply backward induction to compute the optimal bargaining solution related to the cooperation decisions and payments. For the latter case, the MNO can decide the bargaining sequence to maximize its payoff. We explore the structural property of the one-to-many bargaining, and design an Optimal VO Bargaining Sequencing (OVBS) algorithm that computes the optimal bargaining sequence. More precisely, we categorize VOs into three types based on the impact of the Wi-Fi deployment at their venues, and show that it is optimal for the MNO to bargain with these three types of VOs sequentially. Numerical results show that the optimal bargaining sequence improves the MNO's payoff over the random and worst bargaining sequences by up to 14.7% and 45.8%, respectively.
AB - In this paper, we study the cooperative Wi-Fi deployment problem, where the mobile network operator (MNO) cooperates with some venue owners (VOs) to deploy public Wi-Fi networks. The MNO negotiates with the VOs to determine where to deploy Wi-Fi and how much to pay. The MNO's objective is to maximize its payoff, which depends on the payments to VOs, the benefits due to data offloading and mobile advertising, and the costs due to deploying and operating Wi-Fi. We analyze the interactions among the MNO and VOs under the one-to-many bargaining framework, where the MNO bargains with VOs sequentially, taking into account the externalities among different steps of bargaining. We apply the Nash bargaining theory to analyze the cases with exogenous and endogenous bargaining sequences. For the former case, the bargaining sequence is predetermined, and we apply backward induction to compute the optimal bargaining solution related to the cooperation decisions and payments. For the latter case, the MNO can decide the bargaining sequence to maximize its payoff. We explore the structural property of the one-to-many bargaining, and design an Optimal VO Bargaining Sequencing (OVBS) algorithm that computes the optimal bargaining sequence. More precisely, we categorize VOs into three types based on the impact of the Wi-Fi deployment at their venues, and show that it is optimal for the MNO to bargain with these three types of VOs sequentially. Numerical results show that the optimal bargaining sequence improves the MNO's payoff over the random and worst bargaining sequences by up to 14.7% and 45.8%, respectively.
UR - http://www.scopus.com/inward/record.url?scp=84941116473&partnerID=8YFLogxK
U2 - 10.1109/WIOPT.2015.7151092
DO - 10.1109/WIOPT.2015.7151092
M3 - Conference contribution
AN - SCOPUS:84941116473
T3 - 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
SP - 347
EP - 354
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 -