Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144595
Title: A Stackelberg game approach toward socially-aware incentive mechanisms for mobile crowdsensing
Authors: Nie, Jiangtian
Luo, Jun
Xiong, Zehui
Niyato, Dusit
Wang, Ping
Keywords: Engineering::Computer science and engineering
Issue Date: 2018
Source: Nie, J., Luo, J., Xiong, Z., Niyato, D., & Wang, P. (2019). A Stackelberg game approach toward socially-aware incentive mechanisms for mobile crowdsensing. IEEE Transactions on Wireless Communications, 18(1), 724-738. doi:10.1109/twc.2018.2885747
Journal: IEEE Transactions on Wireless Communications
Abstract: Mobile crowdsensing has shown great potential in addressing large-scale data sensing problems by allocating sensing tasks to pervasive mobile users. The mobile users will participate in a crowdsensing platform if they can receive a satisfactory reward. In this paper, to effectively and efficiently recruit a sufficient number of mobile users, i.e., participants, we investigate an optimal incentive mechanism of a crowdsensing service provider. We apply a two-stage Stackelberg game to analyze the participation level of the mobile users and the optimal incentive mechanism of the crowdsensing service provider using backward induction. In order to motivate the participants, the incentive mechanism is designed by taking into account the social network effects from the underlying mobile social domain. We derive the analytical expressions for the discriminatory incentive as well as the uniform incentive mechanisms. To fit into practical scenarios, we further formulate a Bayesian Stackelberg game with incomplete information to analyze the interaction between the crowdsensing service provider and mobile users, where the social structure information, i.e., the social network effects, is uncertain. The existence and uniqueness of the Bayesian Stackelberg equilibrium is analytically validated by identifying the best response strategies of the mobile users. The numerical results corroborate the fact that the network effects significantly stimulate a higher mobile participation level and greater revenue for the crowdsensing service provider. In addition, the social structure information helps the crowdsensing service provider achieve greater revenue gain.
URI: https://hdl.handle.net/10356/144595
ISSN: 1536-1276
DOI: 10.1109/TWC.2018.2885747
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TWC.2018.2885747.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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