Task allocation based on profit maximization for mobile crowdsourcing

doi:10.19682/j.cnki.1005-8885.2020.0007

中国邮电高校学报(英文) ›› 2020, Vol. 27 ›› Issue (1): 26-37.doi: 10.19682/j.cnki.1005-8885.2020.0007

• Computer Applied Technology • 上一篇下一篇

Task allocation based on profit maximization for mobile crowdsourcing

侯莹琳,成卫青

南京邮电大学

收稿日期:2019-09-02 修回日期:2019-12-11 出版日期:2020-02-28 发布日期:2020-02-28
通讯作者: 成卫青 E-mail:chengweiq@njupt.edu.cn
基金资助:
国家自然科学基金

Task allocation based on profit maximization for mobile crowdsourcing

Ying-Lin HOU¹,Wei-Qing CHENG²

1. Nanjing University of Posts and Telecommunications
2.

Received:2019-09-02 Revised:2019-12-11 Online:2020-02-28 Published:2020-02-28
Contact: Wei-Qing CHENG E-mail:chengweiq@njupt.edu.cn
Supported by:
National Natural Science Foundation of China

摘要/Abstract

摘要： In recent years, with the development of smart devices, mobile users can use them to sense the environment. In order to improve the data quality and achieve maximum profits, incentive mechanism is needed to motivate users to participate. In this paper, reputation mechanism, participant selection, task allocation and joint pricing in mobile crowdsourcing system are studied. A user reputation evaluation method is proposed, and a participant selection algorithm (PSA) based on user reputation is proposed. Besides, a social welfare maximization algorithm (SWMA) is proposed, which achieves task pricing with maximizing the interests of all parties, including both task publishers and mobile users. The social welfare maximization problem is divided into local optimization sub-problems which can be solved by double decomposition. It is proved that the algorithm converges to the optimal solution. Results of simulations verify that algorithms PSA and SWMA are effective.

关键词: mobile crowdsourcing, maximum profits, reputation mechanism, task allocation

Abstract: In recent years, with the development of smart devices, mobile users can use them to sense the environment. In order to improve the data quality and achieve maximum profits, incentive mechanism is needed to motivate users to participate. In this paper, reputation mechanism, participant selection, task allocation and joint pricing in mobile crowdsourcing system are studied. A user reputation evaluation method is proposed, and a participant selection algorithm (PSA) based on user reputation is proposed. Besides, a social welfare maximization algorithm (SWMA) is proposed, which achieves task pricing with maximizing the interests of all parties, including both task publishers and mobile users. The social welfare maximization problem is divided into local optimization sub-problems which can be solved by double decomposition. It is proved that the algorithm converges to the optimal solution. Results of simulations verify that algorithms PSA and SWMA are effective.

Key words: mobile crowdsourcing, maximum profits, reputation mechanism, task allocation

中图分类号:

TP39

Ying-Lin HOU Wei-Qing CHENG. Task allocation based on profit maximization for mobile crowdsourcing[J]. The Journal of China Universities of Posts and Telecommunications, 2020, 27(1): 26-37.

参考文献

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Task allocation based on profit maximization for mobile crowdsourcing

Task allocation based on profit maximization for mobile crowdsourcing

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