Multitask Allocation to Heterogeneous Participants in Mobile Crowd Sensing
Joint Authors
Guo, Wenzhong
Zhu, Weiping
Yu, Zhiyong
Xiong, Haoyi
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-14
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Task allocation is a key problem in Mobile Crowd Sensing (MCS).
Prior works have mainly assumed that participants can complete tasks once they arrive at the location of tasks.
However, this assumption may lead to poor reliability in sensing data because the heterogeneity among participants is disregarded.
In this study, we investigate a multitask allocation problem that considers the heterogeneity of participants (i.e., different participants carry various devices and accomplish different tasks).
A greedy discrete particle swarm optimization with genetic algorithm operation is proposed in this study to address the abovementioned problem.
This study is aimed at maximizing the number of completed tasks while satisfying certain constraints.
Simulations over a real-life mobile dataset verify that the proposed algorithm outperforms baseline methods under different settings.
American Psychological Association (APA)
Zhu, Weiping& Guo, Wenzhong& Yu, Zhiyong& Xiong, Haoyi. 2018. Multitask Allocation to Heterogeneous Participants in Mobile Crowd Sensing. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216210
Modern Language Association (MLA)
Zhu, Weiping…[et al.]. Multitask Allocation to Heterogeneous Participants in Mobile Crowd Sensing. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1216210
American Medical Association (AMA)
Zhu, Weiping& Guo, Wenzhong& Yu, Zhiyong& Xiong, Haoyi. Multitask Allocation to Heterogeneous Participants in Mobile Crowd Sensing. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216210
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216210