Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing

By Dejun Yang, Guoliang Xue, Xi Fang, Jian Tang. ACM/IEEE International Conference on Mobile Computing and Networking, 2012

1,031 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Science Applications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4de1ca40f9bad26867601f4d6791bbfbe738653c

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In Automotive Engineering

In Computer Science Applications

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Citations in the corpus

How to crowdsource tasks truthfully without sacrificing utility: Online incentive mechanisms with budget constraint (2014, methodology): “[13] designed an auctionbased incentive mechanism, and proved this mechanism was computationally efficient, individually rational, profitable, and truthful.”
A Learning-Based Incentive Mechanism for Federated Learning (2020, background): “An intuitive idea is to reward participants according to their contributions, following the existing incentive mechanism designs for many other scenarios [5]–[11].”
Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey (2016, methodology): “The authors in [254] modeled an incentive negotiation procedure as a two-stage Stackelberg game with the aim of minimizing the platform’s incentive budget.”
Incentives for Mobile Crowd Sensing: A Survey (2016, background): “[60] consider the essential property of truthfulness in incentive mechanisms, and design a reverse auction-based incentive mechanism that is computationally efficient, individually rational, profitable and truthful:”
A Crowdsourcing Framework for On-Device Federated Learning (2019, background): “g, [34], [35]) and Stackelberg game-based incentive mechanisms such as in [36] and [37].”
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities (2019, background): “Recruitment through incentives: To promote participation and control the rate of recruitment, a set of user incentives can be introduced in MCS [11], [224], [267], [268].”
Mobile Crowd Sensing and Computing (2015, background): “Recently, several game theory approaches [Yang et al. 2012; Lee and Hoh 2010; Huangfu et al. 2013] have been proposed for MCSC to motivate and reward truthful contributions.”
TRAC: Truthful auction for location-aware collaborative sensing in mobile crowdsourcing (2014, background): “Being carried by human users who locate in different places, smartphones can easily collect ubiquitous data and share such data with a large number of potential users [2] [3].”
Incentive Mechanisms for Crowdsensing: Crowdsourcing With Smartphones (2016, background): “Unfortunately, as shown in [45], it is NP-hard to find the optimal solution to the User Selection problem.”
Optimal incentive-driven design of participatory sensing systems (2013, methodology): “Compared to [19], our method explicitly minimizes compensation cost, and it takes into account the computed quality of submitted information.”
CrowdBC: A Blockchain-Based Decentralized Framework for Crowdsourcing (2019, background): “Reputation-based mechanisms are proposed to address “false-reporting” behavior [16], [17], [18].”