Dynamic incentive mechanism in mobile crowdsourcing networks by combining reputation and contract theory. (June 2022)

• Record Type: Journal Article
• Authors: Zhao, Nan; Wan, Qixuan; Chen, Jinlian; Wu, Minghu
• Is Part Of: International journal of distributed sensor networks. Volume 18:Number 6(2022)
• Publication Date: 2022-06
• Subjects: Mobile crowdsourcing network -- long-term incentive mechanism -- asymmetric network information -- dynamic contract design -- reputation incentive design; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/15501329221104352
• Languages: English
• ISSNs: 1550-1329

Abstract

By utilizing the mobile terminals' sensing and computing capabilities, mobile crowdsourcing network is considered to be a promising technology to support the various large-scale sensing applications. However, considering the limited resources and security issue, mobile users may be unwilling to participate in crowdsourcing without any incentive. In this work, by combining reputation and contract theory, a dynamic long-term incentive mechanism is proposed to attract the mobile users to participate in mobile crowdsourcing networks. A two-period dynamic contract is first investigated to deal with the asymmetric information problem in the crowdsourcing tasks. Reputation strategy is then introduced to further attract the mobile users to complete the long-term crowdsourcing tasks. The optimal contracts are designed to obtain the maximum expected utility of service provider with reputation strategy and without reputation strategy, respectively. Simulation results demonstrate that the long-term crowdsourcing tasks can be guaranteed by combining the contract's explicit incentive with the reputation's implicit incentive. The incentive mechanism can gain a higher expected utility, the more implicit reputation effect factor.