An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions

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.

[1]  Jun Zhang,et al.  A Level-Based Learning Swarm Optimizer for Large-Scale Optimization , 2018, IEEE Transactions on Evolutionary Computation.

[2]  Cyrus Shahabi,et al.  A Real-Time Framework for Task Assignment in Hyperlocal Spatial Crowdsourcing , 2017, ACM Trans. Intell. Syst. Technol..

[3]  Jun Zhang,et al.  Distributed Cooperative Co-Evolution With Adaptive Computing Resource Allocation for Large Scale Optimization , 2019, IEEE Transactions on Evolutionary Computation.

[4]  Noboru Sonehara,et al.  Coupons as Monetary Incentives in Participatory Sensing , 2013, I3E.

[5]  Yingshu Li,et al.  Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks , 2018, IEEE Transactions on Dependable and Secure Computing.

[6]  Jiguo Yu,et al.  Latent-Data Privacy Preserving With Customized Data Utility for Social Network Data , 2018, IEEE Transactions on Vehicular Technology.

[7]  Guihai Chen,et al.  Pay as How Well You Do: A Quality Based Incentive Mechanism for Crowdsensing , 2015, MobiHoc.

[8]  Yilong Yin,et al.  A Maximal Clique Based Multiobjective Evolutionary Algorithm for Overlapping Community Detection , 2017, IEEE Transactions on Evolutionary Computation.

[9]  Ioannis Krontiris,et al.  Monetary incentives in participatory sensing using multi-attributive auctions , 2012, Int. J. Parallel Emergent Distributed Syst..

[10]  Hwee Pink Tan,et al.  Incentive Mechanism Design for Heterogeneous Crowdsourcing Using All-Pay Contests , 2016, IEEE Transactions on Mobile Computing.

[11]  Xiang-Yang Li,et al.  Budget-Feasible Online Incentive Mechanisms for Crowdsourcing Tasks Truthfully , 2016, IEEE/ACM Transactions on Networking.

[12]  Zhipeng Cai,et al.  A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems , 2020, IEEE Transactions on Network Science and Engineering.

[13]  Chunyan Miao,et al.  Balancing quality and budget considerations in mobile crowdsourcing , 2016, Decis. Support Syst..

[14]  Jian Tang,et al.  Keep Your Promise: Mechanism Design Against Free-Riding and False-Reporting in Crowdsourcing , 2015, IEEE Internet of Things Journal.

[15]  Yingshu Li,et al.  Truthful Incentive Mechanisms for Social Cost Minimization in Mobile Crowdsourcing Systems , 2016, Sensors.

[16]  Hwee Pink Tan,et al.  Incentive Mechanism Design for Crowdsourcing , 2016, ACM Trans. Intell. Syst. Technol..

[17]  Yingshu Li,et al.  Using crowdsourced data in location-based social networks to explore influence maximization , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[18]  Yingshu Li,et al.  Data Linkage in Smart Internet of Things Systems: A Consideration from a Privacy Perspective , 2018, IEEE Communications Magazine.

[19]  Lei Chen,et al.  Free Market of Crowdsourcing: Incentive Mechanism Design for Mobile Sensing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[20]  Wei Li,et al.  Distributed Auctions for Task Assignment and Scheduling in Mobile Crowdsensing Systems , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[21]  Xi Fang,et al.  Truthful incentive mechanisms for k-anonymity location privacy , 2013, 2013 Proceedings IEEE INFOCOM.

[22]  Yang Gao,et al.  Truthful incentive mechanism with location privacy-preserving for mobile crowdsourcing systems , 2018, Comput. Networks.

[23]  Yang Gao,et al.  An incentive mechanism with privacy protection in mobile crowdsourcing systems , 2016, Comput. Networks.

[24]  Jun Zhang,et al.  Toward Fast Niching Evolutionary Algorithms: A Locality Sensitive Hashing-Based Approach , 2017, IEEE Transactions on Evolutionary Computation.

[25]  Chunyan Miao,et al.  Mitigating Herding in Hierarchical Crowdsourcing Networks , 2016, Scientific Reports.

[26]  Lin Gao,et al.  Providing long-term participation incentive in participatory sensing , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[27]  Liang Liu,et al.  Frugal Online Incentive Mechanisms for Crowdsourcing Tasks Truthfully , 2014, ArXiv.

[28]  Min Liu,et al.  A truthful double auction for two-sided heterogeneous mobile crowdsensing markets , 2016, Comput. Commun..

[29]  Mihaela van der Schaar,et al.  Reputation-based incentive protocols in crowdsourcing applications , 2011, 2012 Proceedings IEEE INFOCOM.

[30]  Liu Yang,et al.  Crowdsourcing Fraud Detection Algorithm Based on Ebbinghaus Forgetting Curve , 2014 .

[31]  Yi Liang,et al.  Deep Learning Based Inference of Private Information Using Embedded Sensors in Smart Devices , 2018, IEEE Network.

[32]  Chunyan Miao,et al.  Algorithmic Management for Improving Collective Productivity in Crowdsourcing , 2017, Scientific Reports.

[33]  Jun Zhang,et al.  AntMapper: An Ant Colony-Based Map Matching Approach for Trajectory-Based Applications , 2018, IEEE Transactions on Intelligent Transportation Systems.

[34]  Xuan Zhu,et al.  A Fair Incentive Mechanism for Crowdsourcing in Crowd Sensing , 2016, IEEE Internet of Things Journal.

[35]  Xi Fang,et al.  Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing , 2012, Mobicom '12.

[36]  Jun Zhang,et al.  Cloudde: A Heterogeneous Differential Evolution Algorithm and Its Distributed Cloud Version , 2017, IEEE Transactions on Parallel and Distributed Systems.

[37]  Baik Hoh,et al.  Sell your experiences: a market mechanism based incentive for participatory sensing , 2010, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[38]  Yingshu Li,et al.  Truthful Incentive Mechanisms for Geographical Position Conflicting Mobile Crowdsensing Systems , 2018, IEEE Transactions on Computational Social Systems.

[39]  Xi Fang,et al.  Incentive Mechanisms for Crowdsensing: Crowdsourcing With Smartphones , 2016, IEEE/ACM Transactions on Networking.

[40]  Chunyan Miao,et al.  Mitigating Herding in Hierarchical Crowdsourcing Networks. , 2016, Scientific reports.

[41]  Xiaomei Zhang,et al.  Movement-Based Incentive for Crowdsourcing , 2017, IEEE Transactions on Vehicular Technology.

[42]  Jianfeng Ma,et al.  RTRC: a reputation-based incentive game model for trustworthy crowdsourcing service , 2016, China Communications.

[43]  Christos H. Papadimitriou,et al.  Free-riding and whitewashing in peer-to-peer systems , 2004, IEEE Journal on Selected Areas in Communications.

[44]  Klara Nahrstedt,et al.  CENTURION: Incentivizing multi-requester mobile crowd sensing , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[45]  Klara Nahrstedt,et al.  Quality of Information Aware Incentive Mechanisms for Mobile Crowd Sensing Systems , 2015, MobiHoc.