Skip to main content

Comparative Analysis of Consensus Algorithms of Blockchain Technology

  • Conference paper
  • First Online:
Ambient Communications and Computer Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1097))

Abstract

In today’s era of big data and machine learning, IoT is playing a very crucial role in nearly all areas like social, economic, political, education, health care. This drastic increase in data creates security, privacy, and trust issues in the era of the Internet. The responsibility of IT is to ensure the privacy and security for huge incoming information and data due to the drastic evolution of the IoT in the coming years. The blockchain has emerged as one of the major technologies that have the potential to transform the way of sharing the huge information and increase trust among. Building trust in a distributed and decentralized environment without the call for a trusted third party is a technological challenge for researchers. Due to the emergence of IoT, the huge and critical information is available over the Internet. The trust over the information is reduced drastically, causing an increase in security and privacy concern day by day. Blockchain is one of the best-emerging technologies for ensuring privacy and security by using cryptographic algorithms and hashing. We will discuss the basics of blockchain technology, consensus algorithms, comparison of important consensus algorithms, and areas of application.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Haber, S., and W. Scott Stornetta. 1991.How to time-stamp a digital document. Journal of Cryptology 3 (2): 99–111.

    Google Scholar 

  2. Nakamoto, S. 2008. Bitcoin: A peer-to-peer electronic cash system, Self-published Paper, May 2008 (Online). Available: https://bitcoin.org/bitcoin.pdf.

  3. Bentov, I., A. Gabizon, and A. Mizrahi. 2016. Cryptocurrencies without proof of work. In International conference on financial cryptography and data security, Christ Church, Barbados, 142–157,Feb 2016.

    Google Scholar 

  4. Castro, M., and B. Liskov. 2002. Practical byzantine fault tolerance and proactive recovery. ACM Transactions on Computer Systems 20 (4): 398–461.

    Article  Google Scholar 

  5. Dai, H., Z. Zheng, and Y. Zhang. Blockchain for ınternet of things: A survey. IEEE Internet of Things Journal. https://doi.org/10.1109/jiot.2019.2920987.

  6. Back, Adam. Hashcash—A denial of service counter-measure. http://www.cypherspace.org/hashcash/.

  7. Vukoli, M. 2016. The quest for scalable blockchain fabric: Proof-of-work vs. BFT replication. IFIP WG 11.4 ınternational workshop on open problems in network security iNetSec 2015, 112–125, 29 Oct 2015–29 Oct 2015.

    Google Scholar 

  8. Jaag, C., and C. Bach. 2017. Blockchain technology and cryptocurrencies opportunities for postal financial services. In The changing postal and delivery sector, 205–221. Springer: Cham. https://doi.org/10.1007/978-3-319-46046-8_13.

  9. Bentov, I., A. Gabizon, and A. Mizrahi. 2016. Cryptocurrencies without proof of work. Paper presented at the ınternational conference on financial cryptography and data security, 142–157. Heidelberg: Springer, February. https://doi.org/10.1007/978-3-662-53357-4_10.

  10. Zheng, Z., S. Xie, H.-N. Dai, and H. Wang. 2016. Blockchain challenges and opportunities: Survey. School of Data and Computer Science, Sun Yat-sen University, Tech. Rep.

    Google Scholar 

  11. Sankar, L.S., M. Sindhu, and M. Sethumadhavan. 2017. Survey of consensus protocols on blockchain applications. In 2017 4th international conference on advanced computing and communication systems (ICACCS).

    Google Scholar 

  12. Larimer, D. 2018. DPOS consensus algorithm—The missing Whitepaper, Steemit (Online). Available: https://steemit.com/dpos/dantheman/dpos-consensus-algorithm-this-missingwhite-paper Accessed 03 Feb 2018.

  13. Correia, M., G. Veronese, and L. Lung. 2010. Asynchronous Byzantine consensus with 2f + 1 processes. In Proceedings of the 2010 ACM symposium on applied computing—SAC ’10.

    Google Scholar 

  14. Theng, Z., S. Xie, H. Dai, X. Chen, and H. Wang. 2017. An overview of blockchain technology: Architecture, consensus, and future trends. In 2017 IEEE international congress on big data (BigData Congress), Honolulu, 557–564, IEEE.

    Google Scholar 

  15. Zheng, Zibin, Shaoan Xie, Hong-Ning Dai, and Xiangping Chen. 2018. Blockchain challenges and opportunities: A survey. Huaimin Wang International Journal of Web and Grid Services (IJWGS) 14 (4).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ashok Kumar Yadav .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yadav, A.K., Singh, K. (2020). Comparative Analysis of Consensus Algorithms of Blockchain Technology. In: Hu, YC., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 1097. Springer, Singapore. https://doi.org/10.1007/978-981-15-1518-7_17

Download citation

Publish with us

Policies and ethics