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Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing
The increasing popularity of portable smart devices has led to the emergence of vehicular crowdsensing as a novel approach for real-time sensing and environmental data collection, garnering significant attention across various domains. Within vehicular crowdsensing, task assignment stands as a funda...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536900/ https://www.ncbi.nlm.nih.gov/pubmed/37765855 http://dx.doi.org/10.3390/s23187798 |
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author | Li, Zhe Liu, Xiaolong Huang, Yang Chen, Honglong |
author_facet | Li, Zhe Liu, Xiaolong Huang, Yang Chen, Honglong |
author_sort | Li, Zhe |
collection | PubMed |
description | The increasing popularity of portable smart devices has led to the emergence of vehicular crowdsensing as a novel approach for real-time sensing and environmental data collection, garnering significant attention across various domains. Within vehicular crowdsensing, task assignment stands as a fundamental research challenge. As the number of vehicle users and perceived tasks grows, the design of efficient task assignment schemes becomes crucial. However, existing research solely focuses on task deadlines, neglecting the importance of task duration. Additionally, the majority of privacy protection mechanisms in the current task assignment process emphasize safeguarding user location information but overlook the protection of user-perceived duration. This lack of protection exposes users to potential time-aware inference attacks, enabling attackers to deduce user schedules and device information. To address these issues in opportunistic task assignment for vehicular crowdsensing, this paper presents the minimum number of participants required under the constraint of probability coverage and proposes the User-Based Task Assignment (UBTA) mechanism, which selects the smallest set of participants to minimize the payment cost while measuring the probability of accomplishing perceived tasks by user combinations. To ensure privacy protection during opportunistic task assignment, a privacy protection method based on differential privacy is introduced. This method fuzzifies the sensing duration of vehicle users and calculates the probability of vehicle users completing sensing tasks, thus avoiding the exposure of users’ sensitive data while effectively assigning tasks. The efficacy of the proposed algorithm is demonstrated through theoretical analysis and a comprehensive set of simulation experiments. |
format | Online Article Text |
id | pubmed-10536900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105369002023-09-29 Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing Li, Zhe Liu, Xiaolong Huang, Yang Chen, Honglong Sensors (Basel) Article The increasing popularity of portable smart devices has led to the emergence of vehicular crowdsensing as a novel approach for real-time sensing and environmental data collection, garnering significant attention across various domains. Within vehicular crowdsensing, task assignment stands as a fundamental research challenge. As the number of vehicle users and perceived tasks grows, the design of efficient task assignment schemes becomes crucial. However, existing research solely focuses on task deadlines, neglecting the importance of task duration. Additionally, the majority of privacy protection mechanisms in the current task assignment process emphasize safeguarding user location information but overlook the protection of user-perceived duration. This lack of protection exposes users to potential time-aware inference attacks, enabling attackers to deduce user schedules and device information. To address these issues in opportunistic task assignment for vehicular crowdsensing, this paper presents the minimum number of participants required under the constraint of probability coverage and proposes the User-Based Task Assignment (UBTA) mechanism, which selects the smallest set of participants to minimize the payment cost while measuring the probability of accomplishing perceived tasks by user combinations. To ensure privacy protection during opportunistic task assignment, a privacy protection method based on differential privacy is introduced. This method fuzzifies the sensing duration of vehicle users and calculates the probability of vehicle users completing sensing tasks, thus avoiding the exposure of users’ sensitive data while effectively assigning tasks. The efficacy of the proposed algorithm is demonstrated through theoretical analysis and a comprehensive set of simulation experiments. MDPI 2023-09-11 /pmc/articles/PMC10536900/ /pubmed/37765855 http://dx.doi.org/10.3390/s23187798 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Zhe Liu, Xiaolong Huang, Yang Chen, Honglong Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title | Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title_full | Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title_fullStr | Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title_full_unstemmed | Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title_short | Probabilistic Coverage Constraint Task Assignment with Privacy Protection in Vehicular Crowdsensing |
title_sort | probabilistic coverage constraint task assignment with privacy protection in vehicular crowdsensing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536900/ https://www.ncbi.nlm.nih.gov/pubmed/37765855 http://dx.doi.org/10.3390/s23187798 |
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