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Trust-Based IoT Cloud Participatory Sensing of Air Quality

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Abstract

In this paper we present a case study of IoT cloud participatory sensing where a user sends a query to the cloud about the air quality of a location at a particular time to decide if it should enter the location based on its susceptibility to the air quality detected. All IoT devices (e.g., smart phones carried by humans or smart cars driven by humans) capable of detecting air quality can act as participants and submit sensing reports to the cloud for sensing result aggregation. The major challenge is the selection of trustworthy participants because not all IoT devices will be trustworthy. We leverage a “Trust as a Service” (TaaS) cloud utility to address the issue of selecting trustworthy participants. Using real traces of ozone (O3) levels and mobility traces of users in the O3 community of interest (O3COI) group in the city of Houston, we demonstrate that TaaS outperforms contemporary IoT trust protocols in selecting trustworthy participants. We compare the performance of the TaaS cloud utility with two contemporary IoT trust protocols for supporting trust-based IoT participatory sensing applications. With the help of the TaaS cloud utility, a user in this O3COI group is able to obtain O3 readings very close to the ground truth O3 level despite 30% participants are untrustworthy.

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References

  1. Khan, W. Z., Xiang, Y., Aalsalem, M. Y., & Arshad, Q. (2013). Mobile phone sensing systems: A survey. IEEE Communications Surveys and Tutorials, 15(1), 402–427.

    Article  Google Scholar 

  2. Mousa, H., et al. (2015). Trust management and reputations systems in mobile participatory sensing applications: A survey. Computer Networks, 90, 49–73.

    Article  Google Scholar 

  3. Amintoosi, H., Kanhere, S. S., & Allahbakhsh, M. (2015). Trust-based privacy-aware participant selection in social participatory sensing. Journal of Information Security and Applications, 20, 11–25.

    Article  Google Scholar 

  4. Al-Hamadi, H., & Chen, I. R. (2017). Trust-based decision making for health IoT systems. IEEE Internet of Things Journal, 4(5), 1408–1419.

    Article  Google Scholar 

  5. Chen, I. R., Guo, J., Wang, D. C., Tsai, J. J. P., Al-Hamadi, H., & You, I. (2018). Trust as a service for IoT service management in smart cities. The 16th IEEE International Conference on Smart City, Exeter, UK, June 2018.

  6. Chen, I. R., Guo, J., & Bao, F. (2016). Trust management for SOA-based IoT and its application to service composition. IEEE Transactions on Services Computing, 9(3), 482–495.

    Article  Google Scholar 

  7. Nitti, M., Girau, R., & Atzori, L. (2014). Trustworthiness management in the social internet of things. IEEE Transactions on Knowledge and Data Management, 26(5), 1253–1266.

    Article  Google Scholar 

  8. Pires B. et al. (2015). Towards an in silico experimental platform for air quality: Houston, TX as a case study. In Computational social science society of America conference, Santa Fe, NM, USA.

  9. Jøsang, A., & Ismail, R. (2002). The beta reputation system. Bled electronic commerce conference, Bled, Slovenia, pp. 1–14.

  10. Guo, J., Chen, I. R., & Tsai. J. J. P. (2017). A mobile cloud hierarchical trust management protocol for IoT systems, In 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, San Francisco, April 2017.

  11. Chen, I. R., Gu, B., George, S. E., & Cheng, S. T. (2005). On failure recoverability of client-server applications in mobile wireless environments. IEEE Transactions on Reliability, 54(1), 115–122.

    Article  Google Scholar 

  12. Gu, B., & Chen, I. R. (2005). Performance analysis of location-aware mobile service proxies for reducing network cost in personal communication systems. Mobile Networks and Applications, 10(4), 453–463.

    Article  Google Scholar 

  13. Cheng, S. T., Chen, C. M., & Chen, I. R. (2000). Dynamic quota-based admission control with sub-rating in multimedia servers. Multimedia Systems, 8(2), 83–91.

    Article  MATH  Google Scholar 

  14. Cheng, S. T., Chen, C. M., & Chen, I. R. (2003). Performance evaluation of an admission control algorithm: Dynamic threshold with negotiations. Performance Evaluation, 52(1), 1–13.

    Article  Google Scholar 

  15. Yilmaz, O., & Chen, I. R. (2009). Utilizing call admission control for pricing optimization of multiple service classes in wireless cellular networks. Computer Communications, 32(2), 317–323.

    Article  Google Scholar 

  16. Chen, I. R., Chen, T. M., & Lee, C. (2001). Agent-based forwarding strategies for reducing location management cost in mobile networks. Mobile Networks and Applications, 6(2), 105–115.

    Article  MATH  Google Scholar 

  17. Chen, I. R., & Wang, D. C. (1996). Analysis of replicated data with repair dependency. The Computer Journal, 39(9), 767–779.

    Article  Google Scholar 

  18. Chen, I. R., Yilmaz, O., & Yen, I. L. (2006). Admission control algorithms for revenue optimization with QoS guarantees in mobile wireless networks. Wireless Personal Communications, 38(3), 357–376.

    Article  Google Scholar 

  19. Chen, I. R., & Bastani, F. B. (1991). Effect of artificial-intelligence planning procedures on system reliability. IEEE Transactions on Reliability, 40(3), 364–369.

    Article  MATH  Google Scholar 

  20. Chen, I. R., Guo, J., Bao, F., & Cho, J. H. (2014). Trust management in mobile Ad Hoc networks for bias minimization and application performance maximization. Ad Hoc Networks, 19, 59–74.

    Article  Google Scholar 

  21. Guo, J., Chen, I. R., & Tsai, J. J. P. (2017). A survey of trust computation models for service management in internet of things systems. Computer Communications, 97, 1–14.

    Article  Google Scholar 

  22. Saied, Y. B., Olivereau, A., Zeghlache, D., & Laurent, M. (2013). Trust management system design for the internet of things: A context-aware and multi-service approach. Computers and Security, 39, 351–365.

    Article  Google Scholar 

  23. Chen, I. R., Bao, F., & Guo, J. (2016). Trust-based service management for social internet of things systems. In IEEE transactions on dependable and secure computing, vol. 13, no. 6, Nov–Dec 2016, (pp. 684–696).

  24. Nitti, M., Atzori, L., & Cvijikj, I. P. (2015). Friendship selection in the social internet of things: Challenges and possible strategies. IEEE Internet of Things Journal, 2(3), 240–247.

    Article  Google Scholar 

  25. Kamvar, S. D., Schlosser,M. T., & Garcia-Molina, H. The EigenTrust algorithm for reputation management in P2P networks. In 12th International conference on world wide web, Budapest, Hungary, 2003.

  26. Xiong, L., & Liu, L. (2004). PeerTrust: Supporting reputation-based trust for peer-to-peer electronic communities. In IEEE transaction on knowledge and data engineering 16, (pp. 843–857).

  27. Su, Z., Liu, L., Li, M., Fan, X., Zhou, Y. ServiceTrust: Trust management in service provision networks. In IEEE international conference on services computing, Santa Clara, CA, USA, 2013, pp. 272-279

  28. Wang, Y., Chen, I. R., & Wang, D. C. (2015). A survey of mobile cloud computing applications: Perspectives and challenges. Wireless Personal Communications, 80, 1607–1623.

    Article  Google Scholar 

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Acknowledgements

This work is supported in part by the U.S. AFOSR under grant number FA2386-17-1-4076.

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Authors and Affiliations

  1. Department of Computer Science, Virginia Tech, Blacksburg, USA

    Jia Guo & Ing-Ray Chen

  2. Department of Information Management, Southern Taiwan University of Science and Technology, Tainan City, Taiwan

    Ding-Chau Wang

  3. Department of Bioinformatics and Biomedical Engineering, Asia University, Taichung City, Taiwan

    Jeffrey J. P. Tsai

  4. Department of Computer Science, Kuwait University, Kuwait City, Kuwait

    Hamid Al-Hamadi

Authors
  1. Jia Guo
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  2. Ing-Ray Chen
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  3. Ding-Chau Wang
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  4. Jeffrey J. P. Tsai
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  5. Hamid Al-Hamadi
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Correspondence to Ing-Ray Chen.

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Guo, J., Chen, IR., Wang, DC. et al. Trust-Based IoT Cloud Participatory Sensing of Air Quality. Wireless Pers Commun 105, 1461–1474 (2019). https://doi.org/10.1007/s11277-019-06154-y

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