Volume 30 Issue 5
Sep.  2021
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JIANG Weijin, LYU Sijian. Dynamic Multi-Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing[J]. Chinese Journal of Electronics, 2021, 30(5): 940-946. doi: 10.1049/cje.2021.07.005
Citation: JIANG Weijin, LYU Sijian. Dynamic Multi-Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing[J]. Chinese Journal of Electronics, 2021, 30(5): 940-946. doi: 10.1049/cje.2021.07.005

Dynamic Multi-Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing

doi: 10.1049/cje.2021.07.005
Funds:

This work is supported by the National Natural Science Foundation of China (No.61772196, No.61472136), the Hunan Provincial Focus Natural Science Fund (No.2020JJ4249), the Key Social Science Fund of Hunan Provincial (No.2016ZDB006), the Key Project of Hunan Provincial Social Science Achievement Review Committee (No.XSP19ZD1005), and the Hunan Province Academic Degree and Graduate Education Reform Research Project (No.2020JGYB234).

  • Received Date: 2020-06-15
    Available Online: 2021-09-02
  • This paper aims to solve the problem of low efficiency, high cost and instability in opportunistic network transmission in the process of mobile group intelligence perception task allocation. Two multi-task dynamic distribution methods based on Lowest cost Participant selection algorithm (LC-PSA) based on user incentive cost and Least number Participant selection algorithm (LN-PSA) based on number of users are proposed respectively. Through these two algorithms, the goal of minimizing the number of people and moving distance required for the task and reducing the system's incentive cost is achieved. Simulation experiments show that compared with similar algorithms, the number of participants in the task distribution scheme selected by the LN-PSA algorithm is reduced by 24.0%, and the system resource consumption is lower, which can provide stable services for the system when users are insufficient in emergencies. Compared with the traditional greedy heuristics algorithm, the LC-PSA algorithm reduces the total system cost by 37.74% and has better overall performance in the comparison experiment.
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