Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2018
Abstract
Spatial crowdsourcing emerges as a new computing paradigm with the development of mobile Internet and the ubiquity of mobile devices. The core of many real-world spatial crowdsourcing applications is to assign suitable tasks to proper workers in real time. Many works only assign a set of tasks to each worker without making the plan how to perform the assigned tasks. Others either make task plans only for a single worker or are unable to operate in real time. In this paper, we propose a new problem called the Multi-Worker-Aware Task Planning (MWATP) problem in the online scenario, in which we not only assign tasks to workers but also make plans for them, such that the total utility (revenue) is maximized. We prove that the offline version of MWATP problem is NP-hard, and no online algorithm has a constant competitive ratio on the MWATP problem. Two heuristic algorithms, called Delay-Planning and Fast-Planning, are proposed to solve the problem. Extensive experiments on synthetic and real datasets verify the effectiveness and efficiency of the two proposed algorithms.
Keywords
Spatial crowdsourcing, Task assignment, Task planning
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Proceedings of the 23rd Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, 2018 May 21-24
First Page
301
Last Page
317
Identifier
10.1007/978-3-319-91458-9_18
Publisher
Springer Link
City or Country
Gold Coast, Australia
Citation
TAO, Qian; ZENG, Yuxiang; ZHOU, Zimu; TONG, Yongxin; CHEN, Lei; and XU, Ke.
Multi-worker-aware task planning in real-time spatial crowdsourcing. (2018). Proceedings of the 23rd Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, 2018 May 21-24. 301-317.
Available at: https://ink.library.smu.edu.sg/sis_research/4735
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-319-91458-9_18