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Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing

Mobile crowdsensing (MCS) has been an emerging sensing paradigm in recent years, which uses a sensing platform for real-time processing to support various services for the Internet of Things (IoT) and promote the development of IoT. As an important component of MCS, how to design task assignment alg...

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Detalles Bibliográficos
Autores principales: Zhang, Mingyuan, Chen, Shiyong, Wei, Zihao, Wu, Yucheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965821/
https://www.ncbi.nlm.nih.gov/pubmed/36850875
http://dx.doi.org/10.3390/s23042275
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author Zhang, Mingyuan
Chen, Shiyong
Wei, Zihao
Wu, Yucheng
author_facet Zhang, Mingyuan
Chen, Shiyong
Wei, Zihao
Wu, Yucheng
author_sort Zhang, Mingyuan
collection PubMed
description Mobile crowdsensing (MCS) has been an emerging sensing paradigm in recent years, which uses a sensing platform for real-time processing to support various services for the Internet of Things (IoT) and promote the development of IoT. As an important component of MCS, how to design task assignment algorithms to cope with the coexistence of multiple concurrent heterogeneous tasks in group-oriented social relationships while satisfying the impact of users’ preferences on heterogeneous multitask assignment and solving the preference matching problem under heterogeneous tasks, is one of the most pressing issues. In this paper, a new algorithm, group-oriented adjustable bidding task assignment (GO-ABTA), is considered to solve the group-oriented bilateral preference-matching problem. First, the initial leaders and their collaborative groups in the social network are selected by group-oriented collaboration, and then the preference assignment of task requesters and users is modeled as a stable preference-matching problem. Then, a tunable bidding task assignment process is completed based on preference matching under budget constraints. Finally, the individual reasonableness, stability, and convergence of the proposed algorithm are demonstrated. The effectiveness of the proposed algorithm and its superiority to other algorithms are verified by simulation results.
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spelling pubmed-99658212023-02-26 Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing Zhang, Mingyuan Chen, Shiyong Wei, Zihao Wu, Yucheng Sensors (Basel) Article Mobile crowdsensing (MCS) has been an emerging sensing paradigm in recent years, which uses a sensing platform for real-time processing to support various services for the Internet of Things (IoT) and promote the development of IoT. As an important component of MCS, how to design task assignment algorithms to cope with the coexistence of multiple concurrent heterogeneous tasks in group-oriented social relationships while satisfying the impact of users’ preferences on heterogeneous multitask assignment and solving the preference matching problem under heterogeneous tasks, is one of the most pressing issues. In this paper, a new algorithm, group-oriented adjustable bidding task assignment (GO-ABTA), is considered to solve the group-oriented bilateral preference-matching problem. First, the initial leaders and their collaborative groups in the social network are selected by group-oriented collaboration, and then the preference assignment of task requesters and users is modeled as a stable preference-matching problem. Then, a tunable bidding task assignment process is completed based on preference matching under budget constraints. Finally, the individual reasonableness, stability, and convergence of the proposed algorithm are demonstrated. The effectiveness of the proposed algorithm and its superiority to other algorithms are verified by simulation results. MDPI 2023-02-17 /pmc/articles/PMC9965821/ /pubmed/36850875 http://dx.doi.org/10.3390/s23042275 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
Zhang, Mingyuan
Chen, Shiyong
Wei, Zihao
Wu, Yucheng
Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title_full Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title_fullStr Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title_full_unstemmed Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title_short Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing
title_sort preference-matched multitask assignment for group socialization under mobile crowdsensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965821/
https://www.ncbi.nlm.nih.gov/pubmed/36850875
http://dx.doi.org/10.3390/s23042275
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