TY - GEN
T1 - A Cross-Space, Multi-interaction-Based Dynamic Incentive Mechanism for Mobile Crowd Sensing
AU - Nan, Wenqian
AU - Guo, Bin
AU - Huangfu, Shenlong
AU - Yu, Zhiwen
AU - Chen, Huihui
AU - Zhou, Xingshe
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - With the surge of varied crowd sensing systems, active user participation becomes a crucial factor that determines whether a crowd sensing system can provide good service quality. To encourage user participation in mobile crowd sensing, we propose a novel incentive mechanism called CSII - a Cross-Space, multi-Interaction-based Incentive mechanism. CSII can estimate the value of a task based on the sensing context and historical data. It then has multiple interactions with both the task requester and the candidate contributors to provide a suggestion on budget and select suitable people to form the worker group. Finally, the requester pays the workers' reward that they deserved by reverse auction based on their reputation and bids. Both online and offline data are leveraged to estimate task value and user quality for a particular task. Experiments show that the incentive mechanism can achieve good performance in terms of acceptance ratio, overpayment ratio, user utility, and so on.
AB - With the surge of varied crowd sensing systems, active user participation becomes a crucial factor that determines whether a crowd sensing system can provide good service quality. To encourage user participation in mobile crowd sensing, we propose a novel incentive mechanism called CSII - a Cross-Space, multi-Interaction-based Incentive mechanism. CSII can estimate the value of a task based on the sensing context and historical data. It then has multiple interactions with both the task requester and the candidate contributors to provide a suggestion on budget and select suitable people to form the worker group. Finally, the requester pays the workers' reward that they deserved by reverse auction based on their reputation and bids. Both online and offline data are leveraged to estimate task value and user quality for a particular task. Experiments show that the incentive mechanism can achieve good performance in terms of acceptance ratio, overpayment ratio, user utility, and so on.
KW - Cross-Space
KW - Incentive Mechanism
KW - Mobile Crowd Sensing
KW - Multi-Interaction
UR - https://www.scopus.com/pages/publications/84949604045
U2 - 10.1109/UIC-ATC-ScalCom.2014.105
DO - 10.1109/UIC-ATC-ScalCom.2014.105
M3 - 会议稿件
AN - SCOPUS:84949604045
T3 - Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014
SP - 179
EP - 186
BT - Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014
A2 - Zheng, Yu
A2 - Thulasiraman, Parimala
A2 - Apduhan, Bernady O.
A2 - Nakamoto, Yukikazu
A2 - Ning, Huansheng
A2 - Sun, Yuqing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Ubiquitous Intelligence and Computing and 11th IEEE International Conference on Autonomic and Trusted Computing and 14th IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014
Y2 - 9 December 2014 through 12 December 2014
ER -