Research Article
A Novel Task Assignment Adjustment Method in Spatial-Temporal Crowdsourcing
@INPROCEEDINGS{10.1007/978-3-031-63992-0_7, author={Bingyi Sun and Jiaxu Cui and Hongtao Bai and Yonggang Zhang}, title={A Novel Task Assignment Adjustment Method in Spatial-Temporal Crowdsourcing}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking and Services. 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14--17, 2023, Proceedings, Part II}, proceedings_a={MOBIQUITOUS PART 2}, year={2024}, month={7}, keywords={Task assignment Spatial-temporal crowdsourcing Multi-objective optimization}, doi={10.1007/978-3-031-63992-0_7} }- Bingyi Sun
Jiaxu Cui
Hongtao Bai
Yonggang Zhang
Year: 2024
A Novel Task Assignment Adjustment Method in Spatial-Temporal Crowdsourcing
MOBIQUITOUS PART 2
Springer
DOI: 10.1007/978-3-031-63992-0_7
Abstract
With the rapid development of mobile networks and the ubiquity of mobile devices, spatial-temporal crowdsourcing, which refers to assigning spatial-temporal tasks to moving workers, has drawn increasing attention. Many researchers aim at various task assignment methods in spatial-temporal crowdsourcing. However, unexpected situations reduce the reliability of the original assignment, such as the absence of reserved workers. To solve the problem, we propose a novel task assignment adjustment method in spatial-temporal crowdsourcing. We design a multi-objective optimization algorithm to minimize the adjustment and maximize the total matching degree in the reassignment process. The experimental results on three real data sets show that the proposed method can improve the total matching degree by about 10% while minimizing the adjustment compared with the baselines.
