| Title |
Mobile Data Offloading In The Vehicular Networks: A Truthful Incentive Mechanism |
| ID_Doc |
37269 |
| Authors |
Enfang Z.; Li P.; Zhang T.; Huang W.; Liu Q. |
| Year |
2019 |
| Published |
Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 |
| DOI |
http://dx.doi.org/10.1109/HPCC/SmartCity/DSS.2019.00306 |
| Abstract |
Mobile data offloading is a cost-effective and promising approach to alleviate the burden of the cellular network. In this paper, we focus on designing a truthful incentive mechanism that the auction cloud platform motivates mobile users with deadline constraints and capacity constraints to offload data. First, we formulate the mobile data offloading problem as a reverse auction. Then, we reduce this social welfare maximization reverse auction for data offloading as an integer linear programming (ILP) problem. To solve this problem, we propose a data offloading auction greedy algorithm to choose the most cost-effective bids. We decompose the data offload auction greedy algorithm into the winner determination problem (WDP) and the threshold payment scheme. Moreover, we propose a delay winner winning algorithm based on the data offloading auction greedy algorithm. Extensive simulation experiments demonstrate that the data offloading auction mechanism dramatically reduces the burden of the cellular network while meeting the offloading tasks deadline constraints and mobile user capacity constraints. © 2019 IEEE. |
| Author Keywords |
Auction theory; Cloud computing; Incentive mechanism; Mobile data offloading; Vehicular networks |
