期刊
IEEE COMMUNICATIONS MAGAZINE
卷 57, 期 2, 页码 54-59出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.2018.1700965
关键词
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资金
- National Natural Science Foundation of China [61872274, 61822207, 61772551, U1636219, 61872431]
- Natural Science Foundation of Hubei Province [2017CFB503, 2017CFA007, 2017CFA047]
- Equipment Pre-Research Joint Fund of Ministry of Education of China (Youth Talent)
- Shandong Provincial Key Program of Research and Development grant [2018GGX101035]
- Fundamental Research Funds for the Central Universities [2042018gf0043]
- State Key Laboratory for Novel Software Technology, Nanjing University [KFKT2018B09]
With the ubiquitous usage of mobile devices, we are witnessing the emergence of commercial crowdsourcing applications that leverage the power of the crowd (workers) to collect massive data. However, the participation unbalance problem commonly occurs in existing location-dependent mobile crowdsourcing applications as workers tend to select nearby tasks while far away tasks are ignored. In this article, we propose a novel task bundling based incentive mechanism that dynamically bundles tasks with different popularity together to solve the participation unbalance problem. We consider the continuous sensing scenarios and categorize tasks into high-popularity (hot) tasks and low-popularity (cold) tasks at each round according to the real-time participation situation of tasks at the last round. We then formulate the task bundling problem as a multi-objective optimization problem, and propose a dynamic task bundling algorithm that dynamically bundles cold tasks with hot tasks at each round. The experimental results demonstrate that the bundling incentive mechanism has a more balanced participation for location-dependent tasks in mobile crowdsourcing systems.
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