Abstract
Mobile crowdsourcing networks (MCNs) are a promising method of data collecting and processing by leveraging the mobile devices’ sensing and computing capabilities. However, because of the selfish characteristics of the service provider (SP) and mobile users (MUs), crowdsourcing participants only aim to maximize their own benefits. This paper investigates the incentive mechanism between the above two parties to create mutual benefits. By modeling MCNs as a labor market, a contract-based crowdsourcing model with moral hazard is proposed under the asymmetric information scenario. In order to incentivize the potential MUs to participate in crowdsourcing tasks, the optimization problem is formulated to maximize the SP’s utility by jointly examining the crowdsourcing participants’ risk preferences. The impact of crowdsourcing participants’ attitudes of risks on the incentive mechanism has been studied analytically and experimentally. Numerical simulation results demonstrate the effectiveness of the proposed contract design scheme for the crowdsourcing incentive.
Highlights
IntroductionAccording to the International Data Corporation, the worldwide smartphone market will reach
According to the International Data Corporation, the worldwide smartphone market will reach1.84 billion units in 2020
Mobile devices in Mobile crowdsourcing networks (MCNs) are always controlled by rational users to maximize their own benefits
Summary
According to the International Data Corporation, the worldwide smartphone market will reach. The SP may not monitor the MUs’ crowdsourcing action in real-time, and the MUs may deviate from the incentive mechanism To tackle this problem, we propose a contract-based incentive mechanism. Moral hazard problems [21] caused by the wireless nodes’ hidden relay actions None of these considered the risk attitudes of crowdsourcing participants (i.e., an SP, or mobile devices). Some MUs may want to “gamble” too much by crowdsourcing sensing, and the crowdsourcing participants’ behavioral features will be influenced by their attitudes on risk Inspired by these existing works, this work investigates the crowdsourcing incentive mechanism in the presence of asymmetric information with risk attitudes. A moral hazard model is proposed to incentivize the MUs to participate in crowdsourcing tasks effectively with asymmetric information.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
