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Participant selection for t-sweep k-coverage crowd sensing tasks

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Abstract

With the popularization of wireless networks and mobile intelligent terminals, mobile crowd sensing is becoming a promising sensing paradigm. Tasks are assigned to users with mobile devices, which then collect and submit ambient information to the server. The composition of participants greatly determines the quality and cost of the collected information. This paper aims to select fewest participants to achieve the quality required by a sensing task. The requirement namely “t-sweep k-coverage” means for a target location, every t time interval should at least k participants sense. The participant selection problem for “t-sweep k-coverage” crowd sensing tasks is NP-hard. Through delicate matrix stacking, linear programming can be adopted to solve the problem when it is in small size. We further propose a participant selection method based on greedy strategy. The two methods are evaluated through simulated experiments using users’ call detail records. The results show that for small problems, both the two methods can find a participant set meeting the requirement. The number of participants picked by the greedy based method is roughly twice of the linear programming based method. However, when problems become larger, the linear programming based method performs unstably, while the greedy based method can still output a reasonable solution.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (No.61300103, 61672159, 61332005), the Technology Innovation Platform Project of Fujian Province under Grant No. 2014H2005 and 2009 J1007,the Fujian Collaborative Innovation Center for Big Data Application in Governments.

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

    Zhiyong Yu, Jie Zhou, Wenzhong Guo & Longkun Guo

  2. Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou, China

    Zhiyong Yu, Jie Zhou & Wenzhong Guo

  3. Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou, 350003, China

    Wenzhong Guo

  4. College of Computer Science, Northwestern Polytechnical University, Xi’an, China

    Zhiwen Yu

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  1. Zhiyong Yu
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Correspondence to Wenzhong Guo.

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This article belongs to the Topical Collection: Special Issue on Mobile Crowdsourcing

Guest Editors: Bin Guo, Xing Xie, Raghu K. Ganti, Daqing Zhang, and Zhu Wang

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Yu, Z., Zhou, J., Guo, W. et al. Participant selection for t-sweep k-coverage crowd sensing tasks. World Wide Web 21, 741–758 (2018). https://doi.org/10.1007/s11280-017-0481-x

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  • DOI: https://doi.org/10.1007/s11280-017-0481-x

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