Quality, Reliability, Security and Robustness in Heterogeneous Systems. 15th EAI International Conference, QShine 2019, Shenzhen, China, November 22–23, 2019, Proceedings

Research Article

Utility-Aware Participant Selection with Budget Constraints for Mobile Crowd Sensing

  • @INPROCEEDINGS{10.1007/978-3-030-38819-5_3,
        author={Shanila Azhar and Shan Chang and Ye Liu and Yuting Tao and Guohua Liu and Donghong Sun},
        title={Utility-Aware Participant Selection with Budget Constraints for Mobile Crowd Sensing},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 15th EAI International Conference, QShine 2019, Shenzhen, China, November 22--23, 2019, Proceedings},
        proceedings_a={QSHINE},
        year={2020},
        month={1},
        keywords={Mobile Crowd Sensing Utility Budget Data quality Incentive},
        doi={10.1007/978-3-030-38819-5_3}
    }
    
  • Shanila Azhar
    Shan Chang
    Ye Liu
    Yuting Tao
    Guohua Liu
    Donghong Sun
    Year: 2020
    Utility-Aware Participant Selection with Budget Constraints for Mobile Crowd Sensing
    QSHINE
    Springer
    DOI: 10.1007/978-3-030-38819-5_3
Shanila Azhar1,*, Shan Chang1,*, Ye Liu1,*, Yuting Tao1,*, Guohua Liu1,*, Donghong Sun2,*
  • 1: Donghua University
  • 2: Tsinghua University
*Contact email: 415029@mail.dhu.edu.cn, changshan@dhu.edu.cn, yeliu@mail.dhu.edu.cn, taoyuting@mail.dhu.edu.cn, ghliu@dhu.edu.cn, sundonghong@tsinghua.edu.cn

Abstract

Mobile Crowd Sensing is an emerging paradigm, which engages ordinary mobile device users to efficiently collect data and share sensed information using mobile applications. The data collection of participants consumes computing, storage and communication resources; thus, it is necessary to give rewards to users who contribute their private data for sensing tasks. Furthermore, since the budget of the sensing task is limited, the Service Provider (SP) needs to select a set of participants such that the total utility of their sensing data can be maximized, and their bid price for sensing data can be satisfied without exceeding the total budget. In this paper, firstly, we claim that the total data utility of a set of participants within a certain area should be calculated according to the data quality of each participant and the location coverage of the sensing data. Secondly, a participant selection scheme has been proposed, which determines a set of participants with maximum total data utility under the budget constraint, and shows that it is a Quadratic Integer Programming problem. Simulations have been conducted to solve the selection problem. The Simulation results demonstrate the effectiveness of the proposed scheme.