Incentive Mechanism Design for WiFi Offloading with Users’ Mobility
Cai Shi-jie①②③ Xiao Li-min②③ Wang Jing②③ Zhou Shi-dong①③
①(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China) ②(Research Institute of Information Technology, Tsinghua University, Beijing 100084, China) ③(Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China)
WiFi network helps offload the traffic pressure in cellular networks and alleviate its traffic congestion. However, it can merely offload the traffic within its coverage. In view of the mobility of users, if the users beyond WiFi coverage are incentivized with certain rewards to postpone their present cellular network services, and wait till they enter WiFi coverage, the traffic offloading capacity of WiFi Network will be significantly enhanced. This paper discusses an incentive mechanism for the operator to encourage users to delay their cellular network services and switch to WiFi network, and formulates the problem as a two-stage Stackelberg game. In this game, an operator expects to adopt an optimum reward solution, giving considerations to the extent of cellular network congestion and the required reward for users. Optimal reward mechanisms for the operators are proposed. According to the research result, the proposed incentive mechanism can effectively reduce the total costs of operators including the cellular network congestion costs and the user reward costs.
Cisco Systems Inc. Cisco visual networking index: global mobile data traffic forecast update, 2011-2016[R]. San Jose, CA, USA, 2012.
[2]
Bennis M, Simsek M, Czylwik A, et al.. When cellular meets WiFi in wireless small cell networks[J]. IEEE Communications Magazine, 2013, 51(6): 44-50.
[3]
Liu Q, Li X R, Xu W J, et al.. Empirical analysis of ZigBee and WiFi coexistence[C]. The 2014 International Conference on Innovative Design and Manufacturing (ICIDM), Montreal, QC, 2014: 117-122.
[4]
Farshad A, Marina M K, and Garcia F. Urban WiFi characterization via mobile crowdsensing[C]. IEEE Network Operations and Management Symposium (NOMS), Krakow, 2014: 1-9.
[5]
Kim Y, Lee K, and Shroff N B. An analytical framework to characterize the efficiency and delay in a mobile data offloading system [C]. MobiHoc, Philadelphia, PA, USA, 2014: 139-149.
[6]
Zhuo X, Gao W, Cao G, et al.. Win-coupon: an incentive framework for 3G traffic offloading[C]. 19th IEEE International Conference on Network Protocols (ICNP), Vancouver, BC Canda, 2011: 206-215.
[7]
Cheung M H and Huang J W. Optimal delayed Wi-Fi offloading[C]. 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Tsukuba Science City, Japan, 2013: 564-571.
[8]
Lee J, Yi Y, Chong S, et al.. Economics of WiFi offloading: trading delay for cellular capacity[J]. IEEE Transactions on Wireless Communications, 2014, 13(3): 1540-1554.
[9]
Lee K, Lee J, Yi Y, et al.. Mobile data offloading: how much can WiFi deliver [J]. IEEE/ACM Transactions on Networking, 2013, 21(2): 536-550.
Liu Li, Jing Tao, and Fu Li. A user-classified method for modeling and analysis of hierarchical cellular networks[J]. Journal of Electronics & Information Technology, 2007, 29(9): 2235-2238.
[11]
Tseng C C, Peng C S, Lo S H, et al.. Co-tier uplink power control in femtocell networks by Stackelberg game with pricing[C]. 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE), Aalborg, 2014: 1-5.
[12]
Fan L F, Friesz T L, Yao T, et al.. Strategic pricing and production planning using a Stackelberg differential game with unknown demand parameters[J]. IEEE Transactions on Engineering Management, 2013, 60(3): 581-591.
[13]
Andrews J G, Baccelli F, and Ganti R K. A tractable approach to coverage and rate in cellular networks [J]. IEEE Transactions on Communications, 2011, 59(11): 3122-3134.
[14]
Gibbens R, Mason R, and Steinberg R. Internet service classes under competition[J]. IEEE Journal on Selected Areas in Communications, 2000, 18(12): 2490-2498.
[15]
Li C T, Wang J K, Wang B, et al.. Cross-layer congestion control algorithm based on compressed sensing in wireless sensor networks[C]. 33rd Chinese Control Conference (CCC), Nanjing, 2014: 5830-5833.
[16]
Mohammadizadeh N and Zhuang W H. Cooperation of heterogeneous wireless networks in end-to-end congestion control for QoS provisioning[C]. IEEE International Conference on Communications (ICC), Budapest, 2013: 6454-6458.
[17]
Islam M, Rahman M L, and Mamun M. Load adaptive congestion control and rate readjustment for wireless mesh networks [C]. 5th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, 2014: 1088-1092.
