Skip to main content

A Survey on Decentralized Crowdsourcing Using Blockchain Technology

  • Chapter
  • First Online:
Further Advances in Internet of Things in Biomedical and Cyber Physical Systems

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 193))

Abstract

Many of the emerging crowd sourcing platforms find central repositories as single point of failure, and are related to the shortcomings of conventional trust-based models. Thanks to involvement of malicious users, they are also vulnerable to distributed denial of service (DDoS) and Sybil attacks. Additionally, high service fees from the community sourcing platform can hinder crowd sourcing growth. It has both research and substantial value for tackling these potential problems. In this article, CrowdBC, a blockchain-based cooperative crowd sourcing system through which a community of employees may solve the requester’s challenge without investing in some third intuition. The safety of consumers is ensured and allows less traction costs. In specific, the new system architecture will be adopted. Implementation of a software model on the public test network Ethereum with real-world dataset. Experiment outcome reveals the viability, efficiency, and scalability of the crowd sourcing method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. To, H., Ghinita, G., Fan, L., Shahabi, C.: Differentially private location protection for worker datasets in spatial crowdsourcing. IEEE Trans. Mob. Comput. 16(4), 934–949 (2017)

    Google Scholar 

  2. Zhuo, G., Jia, Q., Guo, L., Li, M., Li, P.: Privacy-preserving verifiable set operation in big data for cloud-assisted mobile crowdsourcing. IOT J. IEEE 4(2), 572–582 (2017)

    Google Scholar 

  3. Christian, D., Roger, W.: Information propagation in the bit coin network. In: 2013 IEEE Thirteenth International Conference on Peer-to-Peer Computing (P2P), pp. 1–10. IEEE (2013)

    Google Scholar 

  4. Buccafurri, F., Lax, G., Nicolazzo, S., Nocera, A.: Tweetchain: an alternative to blockchain for crowd-based applications. In: International Conference on Web Engineering, pp. 386–393. Springer (2017)

    Google Scholar 

  5. Ouyang, R.W., Kapla, L.M., Toniolo, A., Srivastava, M., Norman, T.J.: Parallel and streaming truth discovery in large-scale quantitative crowdsourcing. IEEE Trans. Parallel Distrib. Syst. 27(10), 1045–9219 (2016)

    Google Scholar 

  6. Feng, W., Yan, Z.: MCS-chain—decentralized and trustworthy mobile crowdsourcing based on blockchain (2019)

    Google Scholar 

  7. Zhang, X., Xue, G., Yu, R., Yang, D., Tang, J.: Keep your promise: mechanism design against free-riding and false-reporting in crowdsourcing. IOT J. IEEE 2(6), 562–572 (2015)

    Google Scholar 

  8. Zhang, Y., van der Schaar, M.: Reputation-based incentive protocols in crowdsourcing applications. In: 2012 Proceedings IEEE INFOCOM, pp. 2140–2148, Florida, USA (2012)

    Google Scholar 

  9. Zhang, S., Wu, J., Lu, S.: Minimum makespan workload dissemination in DTNS: making full utilization of computational surplus around. In: Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 293–296. ACM (2013)

    Google Scholar 

  10. Cheung, M.H., Southwell, R., Hou, F., Huang, J.: Distributed time sensitive task selection in mobile crowd sensing. In: Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 157–166. ACM (2015)

    Google Scholar 

  11. Federico Ast, A.S.: The CrowdJury, a crowd sourced justice system for the collaboration era (2015)

    Google Scholar 

  12. Zhu, H., Zhou, Z.Z.: Analysis and outlook of applications of blockchain technology to equity crowdfunding in china. Financ. Innov. 2(1), 29 (2016)

    Article  Google Scholar 

  13. Vidhyalakshmi, D., Balaji, K.: Performance of bidirectional converter based on grid application. Indonesian J. Electr. Eng. Comput. Sci. 12 (3), 1203 (2018)

    Google Scholar 

  14. Kumar, S.M. and Balakrishnan, G: April. Multi resolution analysis for mass classification in digital mammogram using stochastic neighbor embedding. In 2013 Int. Conf. Commun. Signal Process., (pp. 101–105). IEEE (2013)

    Google Scholar 

  15. Hemalatha, R.J. and Vijayabaskarin, V : Histogram based synovitis scoring system in ultrasound images of rheumatoid arthritis. J. Clin. Diagn. Res., 12(8), (2018)

    Google Scholar 

  16. Pendem, S. and Ramesh, G.P : 75 GHz 5G Frequency spectrum analysis. In Recent Trends and Advances in Artificial Intelligence and Internet of Things (pp. 165–176). Sprin-ger, Cham (2020)

    Google Scholar 

  17. Ramesh G.P., P. S : Design and implementation of U-Shape microstrip patch antenna for bio-medical application. Int. J. Adv. Sci. Tec. 28(12), 364–374

    Google Scholar 

  18. Shahada, S.A.A., Hreiji, S.M., Atudu, S.I. and Shamsudheen, S :2019. Multilayer Neural Network Based Fall Alert System Using IOT. International Journal of MC Square Scientific Research, 11(4), pp.1-15

    Google Scholar 

  19. Badawi, W.A : UNDERGROUND PIPELINE WATER LEAKAGE MONITORING BASED ON IOT. Int. J. MC Square Sci. Res. 11(3), pp.01–08

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Preetha .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Preetha, M., Elavarasi, K., Mani, A., Pavithra, E., Sudharshna, P., Rakshini, S. (2021). A Survey on Decentralized Crowdsourcing Using Blockchain Technology. In: Balas, V.E., Solanki, V.K., Kumar, R. (eds) Further Advances in Internet of Things in Biomedical and Cyber Physical Systems. Intelligent Systems Reference Library, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-030-57835-0_27

Download citation

Publish with us

Policies and ethics