| Title | Bridging the Gap Between Big Data and Game Theory: A General Hierarchical Pricing Framework |
| Authors | Zheng, Zijie Song, Lingyang Han, Zhu |
| Affiliation | Peking Univ, Sch Elect Engn & Comp Sci, Beijing, Peoples R China. Univ Houston, Elect & Comp Engn Dept, Houston, TX USA. |
| Keywords | NETWORK VIRTUALIZATION RESOURCE-ALLOCATION OPTIMIZATION |
| Issue Date | 2017 |
| Publisher | 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) |
| Citation | 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC). 2017. |
| Abstract | In this paper, we propose a general pricing framework, helping the controller promote agents to achieve its objective, for a big data network with one controller and a large number of agents. The convergence of the framework is guaranteed for a general class of objective functions: a separable convex function for the controller and a convex function for each agent. Specially, the proposed framework can converge linearly, when the controller's objective is strongly convex, and the agents' objectives have a uniform Lipschitz gradient. The convergence, and especially the linear convergence is not dependent on the number of agents, which is important for a network with large size. Through numerical results, we apply our pricing framework in a wireless virtualized network to verify its fast convergence, where the pricing framework converges after just a few steps. |
| URI | http://hdl.handle.net/20.500.11897/505286 |
| ISSN | 1550-3607 |
| DOI | 10.1109/ICC.2017.7996334 |
| Indexed | EI CPCI-S(ISTP) |
| Appears in Collections: | 信息科学技术学院 |
