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Task allocation through fuzzy logic based participant density analysis in mobile crowd sensing

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Abstract

Mobile Crowd Sensing (MCS) is an emerging sensing paradigm which employs mobile devices, carried by participants, to sense real-time information. Most previous studies on task allocation in practical applications lack a way of calculating real participant density and making a detailed analysis of it. In this work, first, a fuzzy logic control method is employed to obtain the participant density in different time and space based on participants’ travel time and space. Further, according to the participant density, we can calculate the effective quantity of samples a task requires in a specific time and space. Then, the utility of all tasks can be obtained by considering both the attributes of tasks and the participant-side factors. Last, a hybrid greedy algorithm is proposed to allocate both urgent and non-urgent tasks to ensure the urgent tasks can be allocated as soon as possible and to maximize the utility of all tasks. The simulation results show that the proposed hybrid greedy algorithm is superior to other baselines in terms of the utility of all tasks.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 61602305 and 61802257; and by the Natural Science Foundation of Shanghai under Grant 18ZR1426000 and 19ZR1477600.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Key Lab of Modern Optical System, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Guisong Yang

  2. Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Guisong Yang

  3. Department of Computer Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Yanglin Zhang & Buye Wang

  4. College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Xingyu He

  5. School of Computing & Communications, Lancaster University, Lancaster, LA1 4YW, UK

    Jiangtao Wang

  6. Department of Electrical & Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China

    Ming Liu

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  1. Guisong Yang
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  2. Yanglin Zhang
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Correspondence to Xingyu He.

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Yang, G., Zhang, Y., Wang, B. et al. Task allocation through fuzzy logic based participant density analysis in mobile crowd sensing. Peer-to-Peer Netw. Appl. 14, 763–780 (2021). https://doi.org/10.1007/s12083-020-01047-5

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