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Online Task Allocation in Mobile Crowdsensing with Sweep Coverage and Stability Control

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Part of the book series:Lecture Notes in Computer Science ((LNSC,volume 12487))

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Abstract

Mobile crowdsensing (MCS) harnesses the sensing capabilities of sensors built into a large number of smart devices to collect and analyze data, which can be used by a large number of mobile participants to perform numerous sensing tasks. Stability control and quality coverage are two key issues in mobile crowdsensing as the platform aims to ensure the maximum benefits of the system. However, with the participant’s autonomy and mobility, it is difficult to achieve the quality of coverage in a specific area for task assignment. Furthermore, the stochasticity of tasks causes the stability control being another challenge. To address these issues, in this paper, we design a sweep coverage framework in mobile crowdsensing consisting of a reward rule and a task assignment rule. We first formalize the task queue and participant coverage in the current time slot and introduce disturbance parameters to prevent tasks underflow and waste participant resources. Then, we design a Lyapunov optimization algorithm to solve the stability control and the sweep coverage, which can maintain system stability and achieve a time average social welfare within\( O\left( {1/V} \right) \) of the optimum for a tunable parameter\( V > 0 \). Finally, compared to the random control algorithm and the greedy control algorithm, our algorithm is 40%–50% higher than the greedy control algorithm, and 60%–70% higher than the random control algorithm in terms of social welfare.

This work was supported in part by the National Natural Science Foundation of China (No. 62072411, 61872323, 61751303), in part by the Social Development Project of Zhejiang Provincial Public Technology Research (No. 2017C33054), in part by the Natural Science Foundation of Guangdong Province (No. 2018A030313061), and in part by the Guangdong Science and Technology Plan (no. 2017B010124001, 201902020016, 2019B010139001).

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Zhejiang Normal University, Jinhua, 321004, China

    Jiaang Duan, Jianfeng Lu, Haibo Liu & Shuo Zhang

  2. Xingzhi College, Zhejiang Normal University, Jinhua, 321004, China

    Shasha Yang & Wenchao Jiang

  3. School of Computer, Guangzhou University of Technology, Guangzhou, 510006, China

    Jiaang Duan, Shasha Yang, Jianfeng Lu, Wenchao Jiang, Haibo Liu & Shuo Zhang

Authors
  1. Jiaang Duan

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  2. Shasha Yang

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  3. Jianfeng Lu

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  4. Wenchao Jiang

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  5. Haibo Liu

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  6. Shuo Zhang

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Corresponding author

Correspondence toShasha Yang.

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Duan, J., Yang, S., Lu, J., Jiang, W., Liu, H., Zhang, S. (2020). Online Task Allocation in Mobile Crowdsensing with Sweep Coverage and Stability Control. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12487. Springer, Cham. https://doi.org/10.1007/978-3-030-62460-6_14

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