Incentive Mechanism for Horizontal Federated Learning Based on Reputation and Reverse Auction

Author(s):  
Jingwen Zhang ◽  
Yuezhou Wu ◽  
Rong Pan
Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3453 ◽  
Author(s):  
Ying Hu ◽  
Yingjie Wang ◽  
Yingshu Li ◽  
Xiangrong Tong

In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 1777-1789
Author(s):  
Xiaoqiang Ma ◽  
Weiwei Deng ◽  
Feng Wang ◽  
Menglan Hu ◽  
Fei Chen ◽  
...  

2020 ◽  
Vol 7 (9) ◽  
pp. 8238-8248
Author(s):  
Guoliang Ji ◽  
Zheng Yao ◽  
Baoxian Zhang ◽  
Cheng Li

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