Win-Coupon: An incentive framework for 3G traffic offloading

  • Authors:

  • Xuejun Zhuo;Wei Gao;Guohong Cao;Yiqi Dai

  • Affiliations:

  • Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;The Pennsylvania State University, University Park, State College, PA 16802, USA;The Pennsylvania State University, University Park, State College, PA 16802, USA;Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

  • Venue:
  • ICNP '11 Proceedings of the 2011 19th IEEE International Conference on Network Protocols
  • Year:
  • 2011

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Abstract

3G networks are currently facing severe traffic overload problems caused by excessive demands of mobile users. Offloading part of the 3G traffic through other forms of networks, such as Delay Tolerant Networks (DTNs), WiFi hotspots, and Femtocells, is a promising solution. However, since these networks can only provide intermittent and opportunistic connectivity to mobile users, utilizing them for 3G traffic offloading may result in a non-negligible delay. As the delay increases, the users' satisfaction decreases. In this paper, we investigate the tradeoff between the amount of traffic being offloaded and the users' satisfaction. We provide a novel incentive framework to motivate users to leverage their delay tolerance for 3G traffic offloading. To minimize the incentive cost given an offloading target, users with high delay tolerance and large offloading potential should be prioritized for traffic offloading. To effectively capture the dynamic characteristics of users' delay tolerance, our incentive framework is based on reverse auction to let users proactively express their delay tolerance by submitting bids. We further take DTN as a case study to illustrate how to predict the offloading potential of the users by using stochastic analysis. Extensive trace-driven simulations verify the efficiency of our incentive framework for 3G traffic offloading.