Abstract
Data quality assurance is one of the most critical challenges in the context of Mobile CrowdSensing (MCS). How to effectively select appropriate participants from large-scale candidates to perform sensing tasks while satisfying certain constraint is a problem to be solved. Motivated by this, this paper studies the problem of data-quality-aware participant selection for MCS. Firstly, we propose a quality-aware participant reputation model by introducing active factor to lay a theoretical foundation. Secondly, we present a Multi-Stage Decision solution based on Greedy strategy (MSD-G) to optimize the pending problem while satisfying certain data quality constraint. Extensive simulations over a real dataset verify that our proposed MSD-G can effectively realize participant selection with ideal recruitment cost and sensing data quality.
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References
Guo, B., Zhai, S.Y., Yu, Z.Y.: Crowdsensing big data: sensing data selection, and understanding. Big Data Res. 3(5), 57–69 (2017)
Hu, J., Tao, D.: Theories and methods of quality measure and assurance for mobile crowd sensing. J. Chin. Comput. Syst. 40(5), 918–923 (2019)
Zhao, D., Ma, H.D.: Quality measuring and assurance for mobile crowd sensing. ZTE Technol. J. 21(6), 2–5 (2015)
Zhang, X.L., Yang, Z., Sun, W., Liu, Y.H., et al.: Incentives for mobile crowd sensing: a survey. IEEE Commun. Surv. Tutorials 18(1), 54–67 (2016)
Tao, D., Zhong, S., Luo, H.: Staged incentive and punishment mechanism for mobile crowd sensing. MDPI Sens. 18(7), 1–21 (2018)
Yang, J., Li, P., Wang, H.: Participant reputation aware data collecting mechanism for mobile crowd sensing. In: 2017 IEEE/CIC International Conference on Communications in China (ICCC), Qingdao, pp. 1–6 (2017)
Pournajaf, L., Xiong, L., Sunderam, V., Goryczka, S.: Spatial task assignment for crowd sensing with cloaked locations. In: 15th IEEE International Conference on Mobile Data Management, Brisbane, pp. 73–82 (2014)
Liu, C.H., Zhang, B., Su, X.: Energy-aware participant selection for smartphone-enabled mobile crowd sensing. IEEE Syst. J. 11(3), 1435–1446 (2017)
Zhang, D.Q., Xiong, H.Y., Wang, L.Y.: CrowdRecruiter: selecting participants for piggyback crowdsensing under probabilistic coverage constraint. In: ACM International Joint Conference on Pervasive & Ubiquitous Computing. ACM, Washington (2014)
Acknowledgment
This work was supported by the National Natural Science Foundation of China under Grant No. 61872027. Thanks Prof. Liang Liu in IoT technology laboratory of Beijing University of Posts and Telecommunications for providing all the materials of “KaiTianYan” project.
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Sun, H., Tao, D. (2019). Data-Quality-Aware Participant Selection Mechanism for Mobile Crowdsensing. In: Guo, S., Liu, K., Chen, C., Huang, H. (eds) Wireless Sensor Networks. CWSN 2019. Communications in Computer and Information Science, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-15-1785-3_26
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DOI: https://doi.org/10.1007/978-981-15-1785-3_26
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