Incentive Mechanisms for Crowdsensing: Crowdsourcing With Smartphones

被引:260
作者
Yang, Dejun [1 ]
Xue, Guoliang [2 ]
Fang, Xi [3 ]
Tang, Jian [4 ]
机构
[1] Colorado Sch Mines, Golden, CO 80401 USA
[2] Arizona State Univ, Tempe, AZ 85287 USA
[3] Arizona State Univ, Dept Comp Sci, Tempe, AZ 85281 USA
[4] Syracuse Univ, Syracuse, NY 13244 USA
基金
美国国家科学基金会;
关键词
Crowdsensing; crowdsourcing; incentive mechanism; Stackelberg game; FRAMEWORK;
D O I
10.1109/TNET.2015.2421897
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Smartphones are programmable and equipped with a set of cheap but powerful embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. These sensors can collectively monitor a diverse range of human activities and the surrounding environment. Crowdsensing is a new paradigm which takes advantage of the pervasive smartphones to sense, collect, and analyze data beyond the scale of what was previously possible. With the crowdsensing system, a crowdsourcer can recruit smartphone users to provide sensing service. Existing crowdsensing applications and systems lack good incentive mechanisms that can attract more user participation. To address this issue, we design incentive mechanisms for crowdsensing. We consider two system models: the crowdsourcer-centric model where the crowdsourcer provides a reward shared by participating users, and the user-centric model where users have more control over the payment they will receive. For the crowdsourcer-centric model, we design an incentive mechanism using a Stackelberg game, where the crowdsourcer is the leader while the users are the followers. We show how to compute the unique Stackelberg Equilibrium, at which the utility of the crowdsourcer is maximized, and none of the users can improve its utility by unilaterally deviating from its current strategy. For the user-centric model, we design an auction-based incentive mechanism, which is computationally efficient, individually rational, profitable, and truthful. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our incentive mechanisms.
引用
收藏
页码:1732 / 1744
页数:13
相关论文
共 50 条
  • [41] Incentive mechanism based on Stackelberg game under reputation constraint for mobile crowdsensing
    Yang, Xiaoxiao
    Zhang, Jing
    Peng, Jun
    Lei, Lihong
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2021, 17 (06)
  • [42] Blockchain-Based Efficient Incentive Mechanism in Crowdsensing
    Jiang, Qiulu
    Wan, Wunan
    Qin, Zhi
    Zhang, Jinquan
    Han, Hui
    Zhang, Shibin
    Xia, Jinyue
    [J]. ARTIFICIAL INTELLIGENCE AND SECURITY, ICAIS 2022, PT III, 2022, 13340 : 120 - 132
  • [43] Biobjective Robust Incentive Mechanism Design for Mobile Crowdsensing
    Xu, Jia
    Zhou, Yuanhang
    Ding, Yuqing
    Yang, Dejun
    Xu, Lijie
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (19) : 14971 - 14984
  • [44] Human and Artificial Intelligence Driven Incentive-Operation Model and Algorithms for a Multi-Purpose Integrated Crowdsensing-Crowdsourcing Scalable System
    Greu, Victor
    Ciotirnae, Petric
    Tuta, Leontin
    Popescu, Florin Gabriel
    [J]. 2018 12TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS (COMM), 2018, : 213 - 218
  • [45] A Blockchain-Based Hybrid Incentive Model for Crowdsensing
    Wei, Lijun
    Wu, Jing
    Long, Chengnian
    [J]. ELECTRONICS, 2020, 9 (02)
  • [46] Data Quality Guided Incentive Mechanism Design for Crowdsensing
    Peng, Dan
    Wu, Fan
    Chen, Guihai
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2018, 17 (02) : 307 - 319
  • [47] Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework
    Ogie, R. I.
    [J]. HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES, 2016, 6
  • [48] Online Incentive Mechanisms for Socially-Aware and Socially-Unaware Mobile Crowdsensing
    Ji, Guoliang
    Zhang, Baoxian
    Zhang, Guo
    Li, Cheng
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2024, 23 (05) : 6227 - 6242
  • [49] Incentive mechanism for the listing item task in crowdsourcing
    Wang, Shaofei
    Dang, Depeng
    [J]. INFORMATION SCIENCES, 2020, 512 : 80 - 95
  • [50] An Incentive Mechanism for Crowdsourcing Systems with Network Effects
    Chen, Yanjiao
    Wang, Xu
    Li, Baochun
    Zhang, Qian
    [J]. ACM TRANSACTIONS ON INTERNET TECHNOLOGY, 2019, 19 (04)