@article{oai:muroran-it.repo.nii.ac.jp:00009646,
 author = {OTA,  Kaoru and 太田, 香 and DONG,  Mianxiong and 董, 冕雄 and GUI, Jinsong and LIU, Anfeng},
 issue = {2},
 journal = {IEEE Network},
 month = {Feb},
 note = {application/pdf, Crowd sensing networks play a critical role in big data generation where a large number of mobile devices collect various kinds of data with large-volume features. Although which information should be collected is essential for the success of crowd-sensing applications, few research efforts have been made so far. On the other hand, an efficient incentive mechanism is required to encourage all crowd-sensing participants, including data collectors, service providers, and service consumers, to join the networks. In this article, we propose a new incentive mechanism called QUOIN, which simultaneously ensures Quality and Usability Of INformation for crowd-sensing application requirements. We apply a Stackelberg game model to the proposed mechanism to guarantee each participant achieves a satisfactory level of profits. Performance of QUOIN is evaluated with a case study, and experimental results demonstrate that it is efficient and effective in collecting valuable information for crowd-sensing applications.},
 pages = {114--119},
 title = {QUOIN: Incentive Mechanisms for Crowd Sensing Networks},
 volume = {32},
 year = {2018},
 yomi = {オオタ, カオル and トウ, メンユウ}
}