KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Incentive Mechanism in Participatory Sensing for Ambient Assisted Living

  • Yao, Hu (Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts & Telecommunications) ;
  • Muqing, Wu (Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts & Telecommunications) ;
  • Tianze, Li (Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts & Telecommunications)
  • Received : 2017.03.24
  • Accepted : 2017.09.20
  • Published : 2018.01.31
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Abstract

Participatory sensing is becoming popular and has shown its great potential in data acquisition for ambient assisted living. In this paper, we propose an incentive mechanism in participatory sensing for ambient assisted living, which benefits both the platform and the mobile devices that participated in the sensing task. Firstly, we analyze the profit of participant and platform, and a Stackelberg game model is formulated. The model takes privacy, reputation, power state and quality of data into consideration, and aims at maximizing the profit for both participant and publisher. The discussion of properties of the game show that there exists an unique Stackelberg equilibrium. Secondly, two algorithms are given: one describes how to reach the Stackelberg equilibrium and the other presents the procedures of employing the incentive strategy. Finally, we conduct simulations to evaluate the properties and effectiveness of the proposed mechanism. Simulation results show that the proposed incentive mechanism works well, and the participants and the publisher will be benefitted from it. With the mechanism, the total amount of sensory data can be maximized and the quality of the data can be guaranteed effectively.

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References

  1. D. Cook, S. Das, "Smart Environments: Technologies, Protocols and Applications," Wiley-Interscience, pp. 192-197, 2005.
  2. S. Poslad, "Ubiquitous Computing: Smart Devices, Environments and Interactions," Wiley, Mar. pp. 540-545, 2009.
  3. H. Gao et al., "A Survey of Incentive Mechanisms for Participatory Sensing," in IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 918-943 Secondquarter 2015. https://doi.org/10.1109/COMST.2014.2387836
  4. N. D. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury and A. T. Campbell, "A survey of mobile phone sensing," IEEE Communications Magazine, vol. 48, no. 9, pp. 140-150, Sep. 2010. https://doi.org/10.1109/MCOM.2010.5560598
  5. S. S. Kanhere, "Participatory Sensing: Crowdsourcing Data from Mobile Smartphones in Urban Spaces," in Proc. of 2011 IEEE 12th International Conference on Mobile Data Management, Lulea, pp. 3-6, 2011.
  6. N. Haderer, R. Rouvoy and L. Seinturier, "A preliminary investigation of user incentives to leverage crowdsensing activities," in Proc. of 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), San Diego, CA, pp. 199-204, 2013.
  7. I. Bisio et al.,"A Smartphone-Centric Platform for Remote Health Monitoring of Heart Failure," Wiley International Journal of Communication Systems, Article first published online: 14 Apr. 2014.
  8. Z. Xiao, H. B. Lim and L. Ponnambalam, "Participatory Sensing for Smart Cities: A Case Study on Transport Trip Quality Measurement," IEEE Transactions on Industrial Informatics, vol. 13, no. 2, pp. 759-770, April 2017. https://doi.org/10.1109/TII.2017.2678522
  9. A. D. Mason, G. Michalakidis and P. J. Krause, "Tiger Nation: Empowering citizen scientists," in Proc.2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST), Campione d'Italia, pp. 1-5, 2012.
  10. I. Schweizer, C. Meurisch, J. Gedeon, R. Bartl, and M. Muhlhauser, "Noisemap: Multi-tier incentive mechanisms for participative urban sensing," in Proc. of the Third International Workshop on Sensing Applications on Mobile Phones, PhoneSense '12, ACM, New York, NY, USA, pp. 91-95, Nov.2012.
  11. G. Abdul-Salaam, A. Hanan Abdullah and M. Hossein Anisi, "Energy-Efficient Data Reporting for Navigation in Position-Free Hybrid Wireless Sensor Networks," IEEE Sensors Journal, vol. 17, no. 7, pp. 2289-2297, April 1, 2017. https://doi.org/10.1109/JSEN.2017.2665663
  12. W. Mason, and D. J. Watts, "Financial incentives and the "performance of crowds," in Proc. of the ACM SIGKDD Workshop on Human Computation, HCOMP '09, ACM, New York, NY, USA, pp. 77-85, 2009.
  13. Y. Wang, A. Nakao, and A. V. Vasilakos, "Heterogeneity playing key role: Modeling and analyzing the dynamics of incentive mechanisms in autonomous networks, " ACM Transactions on Autonomous and Adaptive Systems (TAAS), Vol. 7, No. 3, Sep. 2012, Article No. 31.
  14. B. Q. Zhao, J. C. S. Lui and D. M. Chiu, "A Mathematical Framework for Analyzing Adaptive Incentive Protocols in P2P Networks," IEEE/ACM Transactions on Networking, vol. 20, no. 2, pp. 367-380, Apr. 2012. https://doi.org/10.1109/TNET.2011.2161770
  15. E. Huang, J. Crowcroft, and I. Wassell, "Rethinking incentives for mobile ad hoc networks," in Proc. Proceedings of the ACM SIGCOMM Workshop on Practice and Theory of Incentives in Networked Systems, PINS '04, ACM, New York, NY, USA, 2004, pp. 191-196.
  16. Z. Song, C. H. Liu, J. Wu, J. Ma and W. Wang, "QoI-Aware Multitask-Oriented Dynamic Participant Selection With Budget Constraints," IEEE Transactions on Vehicular Technology, vol. 63, no. 9, pp. 4618-4632, Nov. 2014. https://doi.org/10.1109/TVT.2014.2317701
  17. C. H. Liu, J. Fan, P. Hui, J. Crowcroft and G. Ding, "QoI-Aware Energy-Efficient Participatory Crowdsourcing," IEEE Sensors Journal, vol. 13, no. 10, pp. 3742-3753, Oct. 2013. https://doi.org/10.1109/JSEN.2013.2265936
  18. D. Zhao, H. Ma and L. Liu, "Frugal Online Incentive Mechanisms for Mobile Crowd Sensing," IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3319-3330, April 2017. https://doi.org/10.1109/TVT.2016.2587722
  19. Y. Lv, and T. Moscibroda, "Fair and resilient incentive tree mechanisms," in Proc. Proceedings of the 2013 ACM Symposium on Principles of Distributed Computing, PODC '13, ACM, New York, NY, USA, 2013, pp. 230-239.
  20. B. Faltings, J. J. Li and R. Jurca, "Incentive Mechanisms for Community Sensing," IEEE Transactions on Computers, vol. 63, no. 1, pp. 115-128, Jan. 2014. https://doi.org/10.1109/TC.2013.150
  21. Y. Zhang and M. van der Schaar, "Reputation-based incentive protocols in crowdsourcing applications," 2012 Proceedings IEEE INFOCOM, Orlando, FL, pp. 2140-2148, 2012.
  22. A. Albers, I. Krontiris, N. Sonehara, and I. Echizen, "Coupons as monetary incentives in participatory sensing," in Proc. Collaborative, Trusted and Privacy-Aware e/m-Services, Springer, 2013, pp. 226-237.
  23. K. L. Huang, S. S. Kanhere, and W. Hu, "On the need for a reputation system in mobile phone based sensing," Ad Hoc Networks, Vol. 12, pp. 130-149, Jan. 2014. https://doi.org/10.1016/j.adhoc.2011.12.002
  24. Y. Zhang and M. van der Schaar, "Robust Reputation Protocol Design for Online Communities: A Stochastic Stability Analysis," IEEE Journal of Selected Topics in Signal Processing, vol. 7, no. 5, pp. 907-920, Oct. 2013. https://doi.org/10.1109/JSTSP.2013.2263785
  25. Q. Li and G. Cao, "Providing privacy-aware incentives for mobile sensing," in Proc. of 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom), San Diego, CA, pp. 76-84, 2013.
  26. X. Oscar Wang, W. Cheng, P. Mohapatra and T. Abdelzaher, "ARTSense: Anonymous reputation and trust in participatory sensing," 2013 Proceedings IEEE INFOCOM, Turin, 2013, pp. 2517-2525.
  27. X. Zhang, Z. Yang, Z. Zhou, H. Cai, L. Chen and X. Li, "Free Market of Crowdsourcing: Incentive Mechanism Design for Mobile Sensing," IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 12, pp. 3190-3200, Dec. 2014. https://doi.org/10.1109/TPDS.2013.2297112
  28. D. Zhao, X. Y. Li and H. Ma, "How to crowdsource tasks truthfully without sacrificing utility: Online incentive mechanisms with budget constraint," in Proc. IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, Toronto, ON, pp. 1213-1221, 2014.
  29. R. T. B. Ma, S. C. M. Lee, J. C. S. Lui and D. K. Y. Yau, "Incentive and Service Differentiation in P2P Networks: A Game Theoretic Approach," IEEE/ACM Transactions on Networking, vol. 14, no. 5, pp. 978-991, Oct. 2006. https://doi.org/10.1109/TNET.2006.882904
  30. W. S. Lin, H. V. Zhao and K. J. R. Liu, "Incentive Cooperation Strategies for Peer-to-Peer Live Multimedia Streaming Social Networks," IEEE Transactions on Multimedia, vol. 11, no. 3, pp. 396-412, April 2009. https://doi.org/10.1109/TMM.2009.2012915
  31. W. Tushar, W. Saad, H. V. Poor and D. B. Smith, "Economics of Electric Vehicle Charging: A Game Theoretic Approach," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1767-1778, Dec. 2012. https://doi.org/10.1109/TSG.2012.2211901
  32. H. Park and M. van der Schaar, "Coalition-Based Resource Negotiation for Multimedia Applications in Informationally Decentralized Networks," in IEEE Transactions on Multimedia, vol. 11, no. 4, pp. 765-779, Jun. 2009. https://doi.org/10.1109/TMM.2009.2017638
  33. D. Christin, A. Reinhardt, S. S. Kanhere, and M. Hollick, "A survey on privacy in mobile participatory sensing applications," Journal of Systems and Software, Vol. 84, Iss. 11, pp. 1928-1946, Nov. 2011. https://doi.org/10.1016/j.jss.2011.06.073
  34. Li Tianze, Wu Muqing and Wu Yuewei, "An game theory based online incentive mechanism for participatory sensing," in Proc. of 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, pp. 700-705, 2016.