Incentive mechanism design for edge‐cloud collaboration in mobile crowd sensing

2020 ◽  
Author(s):  
Zhuo Li ◽  
Lihan Zhang ◽  
Xin Chen
Keyword(s):  
Mechanism Design ◽  
Incentive Mechanism ◽  
Mobile Crowd Sensing ◽  
Crowd Sensing ◽  
Incentive Mechanism Design ◽  
Mobile Crowd

scholarly journals Staged Incentive and Punishment Mechanism for Mobile Crowd Sensing

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2391 ◽  
Author(s):  
Dan Tao ◽  
Shan Zhong ◽  
Hong Luo
Keyword(s):  
Incentive Mechanism ◽  
Extensive Study ◽  
Mobile Crowd Sensing ◽  
Space Correlation ◽  
Data Utility ◽  
Sensing Data ◽  
Crowd Sensing ◽  
Time Space ◽  
Punishment Mechanism ◽  
Mobile Crowd

Having an incentive mechanism is crucial for the recruitment of mobile users to participate in a sensing task and to ensure that participants provide high-quality sensing data. In this paper, we investigate a staged incentive and punishment mechanism for mobile crowd sensing. We first divide the incentive process into two stages: the recruiting stage and the sensing stage. In the recruiting stage, we introduce the payment incentive coefficient and design a Stackelberg-based game method. The participants can be recruited via game interaction. In the sensing stage, we propose a sensing data utility algorithm in the interaction. After the sensing task, the winners can be filtered out using data utility, which is affected by time–space correlation. In particular, the participants’ reputation accumulation can be carried out based on data utility, and a punishment mechanism is presented to reduce the waste of payment costs caused by malicious participants. Finally, we conduct an extensive study of our solution based on realistic data. Extensive experiments show that compared to the existing positive auction incentive mechanism (PAIM) and reverse auction incentive mechanism (RAIM), our proposed staged incentive mechanism (SIM) can effectively extend the incentive behavior from the recruiting stage to the sensing stage. It not only achieves being a real-time incentive in both the recruiting and sensing stages but also improves the utility of sensing data.

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