A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing

With the powerful sensing, computing capabilities of mobile devices, large-scale users with smart devices throughout the city would be the perfect carrier for the people-centric scheme, namely, mobile crowdsensing. Mobile crowdsensing has become a versatile platform for many Internet of things appli...

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Main Authors: Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang
Format: Article
Language:English
Published: Wiley 2022-09-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/15501329221123531
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author Yang Liu
Yong Li
Wei Cheng
Weiguang Wang
Junhua Yang
author_facet Yang Liu
Yong Li
Wei Cheng
Weiguang Wang
Junhua Yang
author_sort Yang Liu
collection DOAJ
description With the powerful sensing, computing capabilities of mobile devices, large-scale users with smart devices throughout the city would be the perfect carrier for the people-centric scheme, namely, mobile crowdsensing. Mobile crowdsensing has become a versatile platform for many Internet of things applications in urban scenarios. So how to select the appropriate users to complete the tasks and ensure the quality of the tasks has been a huge challenge for mobile crowdsensing. In this article, we propose a willingness-aware user recruitment strategy based on the task attributes to solve this problem. First, we divide the whole sensing region based on task attributes by a weighted Voronoi diagram and conduct the assessment about the sub-regions according to several parameters, and then categorize sub-regions as hot regions and blank regions. Moreover, we analyze the influence of user willingness on user recruitment and the task completion rate and assess the coverage ability of the users. Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. Simulation results show that the willingness-aware user recruitment approach can significantly improve the task completion rate and achieve higher task coverage quality compared with other algorithms.
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issn 1550-1477
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publishDate 2022-09-01
publisher Wiley
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series International Journal of Distributed Sensor Networks
spelling doaj-art-8755eac4e7254a8690fdbcc45dd3c86c2025-08-20T02:09:02ZengWileyInternational Journal of Distributed Sensor Networks1550-14772022-09-011810.1177/15501329221123531A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensingYang Liu0Yong Li1Wei Cheng2Weiguang Wang3Junhua Yang4School of Electronics and Information, Northwestern Polytechnical University, Xi’an, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, ChinaSchool of Electronic Engineering, Xi’an University of Posts and Telecommunications, Xi’an, ChinaWith the powerful sensing, computing capabilities of mobile devices, large-scale users with smart devices throughout the city would be the perfect carrier for the people-centric scheme, namely, mobile crowdsensing. Mobile crowdsensing has become a versatile platform for many Internet of things applications in urban scenarios. So how to select the appropriate users to complete the tasks and ensure the quality of the tasks has been a huge challenge for mobile crowdsensing. In this article, we propose a willingness-aware user recruitment strategy based on the task attributes to solve this problem. First, we divide the whole sensing region based on task attributes by a weighted Voronoi diagram and conduct the assessment about the sub-regions according to several parameters, and then categorize sub-regions as hot regions and blank regions. Moreover, we analyze the influence of user willingness on user recruitment and the task completion rate and assess the coverage ability of the users. Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. Simulation results show that the willingness-aware user recruitment approach can significantly improve the task completion rate and achieve higher task coverage quality compared with other algorithms.https://doi.org/10.1177/15501329221123531
spellingShingle Yang Liu
Yong Li
Wei Cheng
Weiguang Wang
Junhua Yang
A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
International Journal of Distributed Sensor Networks
title A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
title_full A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
title_fullStr A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
title_full_unstemmed A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
title_short A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing
title_sort willingness aware user recruitment strategy based on the task attributes in mobile crowdsensing
url https://doi.org/10.1177/15501329221123531
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