An Optimization and Auction-Based Incentive Mechanism to Maximize Social Welfare for Mobile Crowdsourcing

被引：115

作者：

Wang, Yinjie ^{[1
]}

Cai, Zhipeng ^{[2
]}

Zhan, Zhi-Hui ^{[3
,4
]}

Gong, Yue-Jiao ^{[3
,4
]}

Tong, Xiangrong ^{[1
]}

机构：

[1] Yantai Univ, Sch Comp & Control Engn, Yantai 264005, Peoples R China

[2] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA

[3] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510006, Guangdong, Peoples R China

[4] South China Univ Technol, Guangdong Prov Key Lab Computat Intelligence & Cy, Guangzhou 510006, Guangdong, Peoples R China

来源：

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS | 2019年 / 6卷 / 03期

基金：

美国国家科学基金会; 中国国家自然科学基金; 中国博士后科学基金;

关键词：

Incentive mechanism; mobile crowdsourcing; social welfare; task selection; worker selection;

D O I：

10.1109/TCSS.2019.2907059

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Mobile crowdsourcing is an emerging crowdsourcing paradigm, which generates large-scale sensing tasks and sensing data. One of the major issues in mobile crowdsourcing is how to maximize social welfare through selecting appropriate sensing tasks for crowd workers and selecting appropriate workers for sensing tasks such that it can improve the effectiveness and efficiency of mobile crowdsourcing. This paper proposes an incentive mechanism to maximize social welfare for mobile crowdsourcing and, respectively, investigates worker-centric task selection and platform-centric worker selection. This paper applies an optimization algorithm in task selection for mobile crowdsourcing systems. A discrete particle swarm optimization (DPSO) algorithm for worker-centric task selection is designed to maximize the utilities of workers. In addition, a platform-centric worker selection method, which integrates multiattribute auction and two-stage auction, is proposed to maximize the utility of the platform. The performance of the proposed incentive mechanism is evaluated through experiments. The experimental results show that the proposed incentive mechanism can improve the efficiency and truthfulness of mobile crowdsourcing effectively.

引用

页码：414 / 429

页数：16

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