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Socially-aware and privacy-preserving multi-objective worker recruitment in mobile crowd sensing

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Abstract

With the increasing popularity of mobile smart devices, Mobile Crowd Sensing (MCS) has gained significant attention from the research community. Worker recruitment is a key research problem in MCS systems, where platforms recruit suitable workers for tasks in specified locations. A recently proposed approach to worker recruitment is the socially-aware MCS model, which utilizes workers’ social connections to expand the platform’s worker pool. This approach effectively improves the quality of task sensing. In the past, most worker recruitment ignored the combined utility of all parties and the privacy of the worker location, instead considering the interests of only one of the task requesters, the platform, or the worker. Therefore, we propose a Socially-Aware and Privacy-Preserving Multi-Objective Worker Recruitment (SPMWR) model. The objective is to use social network-assisted recruitment to weigh the interests of workers and platforms while protecting worker location information. To address the model, we first introduce a differential privacy mechanism to protect worker location information. Then the Weighted Combinatorial Multi-Objective Genetic Algorithm (WCMOGA) is proposed, aiming to discover potentially better worker selection options as much as possible. The effectiveness of SPMWR is verified through comparative experiments on different scenarios with real data sets.

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Acknowledgements

All authors consent to the publication of the manuscript.

Funding

This research is supported by the National Natural Science Foundation of China (Grant Nos. 61962005).

Author information

Authors and Affiliations

  1. School of Computer Electronics and Information, Guangxi University, Nanning, 530004, China

    Yanming Fu, Shenglin Lu, Jiayuan Chen, Xiao Liu & Bocheng Huang

  2. Key Laboratory of Parallel Distributed and Intelligent Computing, Nanning, 530004, China

    Yanming Fu, Shenglin Lu, Jiayuan Chen, Xiao Liu & Bocheng Huang

  3. Guangxi Intelligent Digital Services Research Center of Engineering Technology, Nanning, 530004, China

    Yanming Fu, Shenglin Lu, Jiayuan Chen, Xiao Liu & Bocheng Huang

Authors
  1. Yanming Fu
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  2. Shenglin Lu
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  3. Jiayuan Chen
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  4. Xiao Liu
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  5. Bocheng Huang
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Contributions

Yanming Fu provided valuable comments on the overall scheme and did the writing, reviewing, and editing work. Shenglin Lu formulated the detailed problem, designed the algorithm scheme, did simulation experiments as well as debugging work, and prepared the original draft. Jiayuan Chen participated in the design and improvement and review of some of the schemes. Xiao Liu and Bocheng Huang participated in writing, reviewing and perfecting the work.

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Correspondence to Shenglin Lu.

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This manuscript describes original work and is not under consideration by any other journal. All authors approved the manuscript and this submission.

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Fu, Y., Lu, S., Chen, J. et al. Socially-aware and privacy-preserving multi-objective worker recruitment in mobile crowd sensing. Peer-to-Peer Netw. Appl. 17, 1001–1019 (2024). https://doi.org/10.1007/s12083-024-01652-8

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  • DOI: https://doi.org/10.1007/s12083-024-01652-8

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