Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 69, Issue 2, Pages 2219-2229Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2962064
Keywords
Task allocation; efficient cooperation; crowdsensing
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Funding
- Funds for International Cooperation and Exchange of NSFC [61720106007]
- National Natural Science Foundation of China [61732017, 61972044]
- 111 Project [B18008]
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With the explosive growth of mobile devices, it is convenient for participants to perform mobile crowd sensing (MCS) tasks. It is a useful way to recruit participants to perform location-dependent tasks. We first investigate Min-Max Task Planning (MMTP) problem on time-sensitive MCS systems, considering time-sensitivity and heterogeneity of sensing tasks, and people-variability of the participants. Namely, how to design a cooperation method for the participants so that they spend as little time as possible. To address the MMTP problem, we propose a Memetic based Bidirectional General Variable Neighborhood Search (MB-GVNS) algorithm, in which all tasks are separated into groups and traveling path is planned for each participant. Moreover, we consider the task in both people-invariable and people-variable scenarios. Finally, extensive experiments are conducted to demonstrate the benefits of our method, outperforming other similar state-of-the-art algorithms.
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