Task Distribution Method of Participatory Sensing Based on Urban Rail Transit

Weijin JIANG; Sijian LÜ; Yuehua LIU; Junpeng CHEN; Wanqing ZHANG

doi:10.11999/JEIT200510

Volume 43 Issue 10

Oct. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(10): 3035-3042

Weijin JIANG, Sijian LÜ, Yuehua LIU, Junpeng CHEN, Wanqing ZHANG. Task Distribution Method of Participatory Sensing Based on Urban Rail Transit[J]. Journal of Electronics & Information Technology, 2021, 43(10): 3035-3042. doi: 10.11999/JEIT200510

Citation:

Weijin JIANG, Sijian LÜ, Yuehua LIU, Junpeng CHEN, Wanqing ZHANG. Task Distribution Method of Participatory Sensing Based on Urban Rail Transit[J]. Journal of Electronics & Information Technology, 2021, 43(10): 3035-3042. doi: 10.11999/JEIT200510

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Task Distribution Method of Participatory Sensing Based on Urban Rail Transit

doi: 10.11999/JEIT200510

1.
College of Computer and Information Engineering, Hunan University of Technology and Business, Changsha 410205, China
2.
Institute of Big Data and Internet Innovation, Hunan University of Technology and Business, Changsha 410205, China

Funds: The National Natural Science Foundation of China (61772196, 61472136), The Hunan Provincial Focus Natural Science Fund (2020JJ4249), The Hunan Provincial Focus Social Science Fund (2016ZDB006), The Key Project of Hunan Provincial Social Science Achievement Review Committee (XSP 19ZD1005), The Degree and Graduate Education Reform Research Project of Hunan Provincial (2020JGYB234), The Hunan Provincial Department of Education Science Research Fund (20A131)

Received Date: 2020-06-23
Rev Recd Date: 2021-05-28

Available Online: 2021-07-13

Publish Date: 2021-10-18

Abstract

Abstract

With the current development of mobile terminal devices and the popularity of 5G technology, there is an increasing demand for mobile group intelligence awareness. However, the current distribution methods for sensing tasks still suffer from inefficient, costly and unstable transmission, which limits greatly the completion of sensing terminal tasks. For this reason, an Incentive Cost Task Distribution Model (ICTDM) and a User Number Task Distribution Model (UNTDM) based on the good coverage of urban rail transit and the predictability of urban rail transit are proposed. The selective distribution of sensory tasks in different areas of the city is achieved through the sparseness of rail traffic for aggregated pedestrian flows. And the minimization of the number of people required for the task and the distance moved is used as a means to accomplish the purpose of reducing the total incentive cost of the system. Experimental results show that this algorithm can achieve fewer task participant distribution schemes by optimizing the task distribution process to reduce the cost of perceived tasks compared with similar algorithms, while completing the same set of tasks.
- Data crowdsourcing,
- Mobile Internet of Things (IoT),
- Participatory sensing,
- Task distribution,
- Urban rail transit

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References(16)

References

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