Task bundling in worker‐centric mobile crowdsensing

Zhao, Tianlu ORCID: https://orcid.org/0000-0003-4596-7648, Yang, Yongjian ORCID: https://orcid.org/0000-0002-0056-3626, Wang, En ORCID: https://orcid.org/0000-0001-6112-2923, Mumtaz, Shahid ORCID: https://orcid.org/0000-0001-6364-6149 and Cheng, Xiaochun ORCID: https://orcid.org/0000-0003-0371-9646 (2021) Task bundling in worker‐centric mobile crowdsensing. International Journal of Intelligent Systems, 36 (9) . pp. 4936-4961. ISSN 0884-8173 [Article] (doi:10.1002/int.22497)

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Abstract

Most existing research about task allocation in mobile crowdsensing mainly focus on requester-centric mobile crowdsensing (RCMCS), where the requester assigns tasks to workers to maximize his/her benefits. A worker in RCMCS might suffer benefit damage because the tasks assigned to him/her may not maximize his/her benefit. Contrarily, worker-centric mobile crowdsensing (WCMCS), where workers autonomously select tasks to accomplish to maximize their benefits, does not receive enough attention. The workers in WCMCS can maximize their benefits, but the requester in WCMCS will suffer benefit damage (cannot maximize the number of expected completed tasks). It is hard to maximize the number of expected completed tasks in WCMCS, because some tasks may be selected by no workers, while others may be selected by many workers. In this paper, we apply task bundling to address this issue, and we formulate a novel task bundling problem in WCMCS with the objective of maximizing the number of expected completed tasks. To solve this problem, we design an algorithm named LocTrajBundling which bundles tasks based on the location of tasks and the trajectories of workers. Experimental results show that, compared with other algorithms, our algorithm can achieve a better performance in maximizing the number of expected completed tasks.

Item Type: Article
Keywords (uncontrolled): Theoretical Computer Science, Human-Computer Interaction, Software, Artificial Intelligence
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 33402
Notes on copyright: This is the peer reviewed version of the following article: Zhao, T, Yang, Y, Wang, E, Mumtaz, S, Cheng, X. Task bundling in worker-centric mobile crowdsensing. Int J Intell Syst. 2021; 36: 4936- 4961, which has been published in final form at https://doi.org/10.1002/int.22497. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions
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Depositing User: Jisc Publications Router
Date Deposited: 14 Jun 2021 08:06
Last Modified: 13 Sep 2021 16:24
URI: https://eprints.mdx.ac.uk/id/eprint/33402

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