From Traditional Fault Tolerance to Blockchain. Wenbing Zhao
Чтение книги онлайн.

Читать онлайн книгу From Traditional Fault Tolerance to Blockchain - Wenbing Zhao страница 13

СКАЧАТЬ and efficient manner by separating the safety concern and the liveness concern [9]. Additional Paxos algorithm are developed to minimize the resources required, and to reduce the latency for achieving consensus by using a higher redundancy level [10, 18].

      Chapter 7 introduces the problem of Byzantine fault tolerance. A Byzantine fault is synonymous with a malicious fault. Because a malicious faulty component may choose to behave like any of the non-malicious faults, the Byzantine fault model encompasses any arbitrary fault. The distributed consensus problem under the Byzantine fault model was first studied several decades ago by Lamport, Shostak, and Pease [11]. A much more efficient algorithm for achieving fault tolerance under the Byzantine fault model (referred to as Practical Byzantine fault tolerance) was proposed by Castro and Liskov in 1999 [5]. Since then, the research on Byzantine fault tolerance exploded. With the pervasiveness of cyberattacks and espionages, dealing with malicious faults becomes an urgent concern now compared with several decades ago.

      Chapter 8 provides an overview of cryptocurrency and the blockchain technology, including the early conception of cryptocur rency, the first implementation of cryptocurrency in Bitcoin [12], the concept of smart contract and its implementation in Ethereum [4], as well as the vision of decentralized organizations [16] powered by smart contract and the blockchain technology.

      Chapter 10 presents the applications of the blockchain technology and issues that will directly impact on how widely the blockchain technology can be adopted, including the value of the blockchain technology and the efforts to increase the throughput of blockchain systems [1, 3, 14, 21]. We primarily focus on blockchain applications in the area of cyber-physical systems (CPS) [20]. CPS is evolving rapidly and the integration of blockchain and CPS could potentially transform CPS design for much stronger security and robustness.

      Wenbing Zhao

      Cleveland, USA

      March 2021

      References

      1 1. E. Akbari, W. Zhao, S. Yang, and X. Lou. The impact of block parameters on the throughput and security of blockchains. In Proceedings of the 2020 International Conference on Blockchain Technology, pages 13–18. ACM, 2020.

      2 2. A. Arnold. Assessing the financial impact of downtime, April 2010. http://www.businesscomputingworld.co.uk/assessing-the-financial-impact-of-downtime/.

      3 3. A. Back, M. Corallo, L. Dashjr, M. Friedenbach, G. Maxwell, A. Miller, A. Poelstra, J. Timón, and P. Wuille. Enabling blockchain innovations with pegged sidechains. URL: http://www.opensciencereview.com/papers/123/enablingblockchain-innovations-with-pegged-sidechains, 72, 2014.

      4 4. V. Buterin et al. Ethereum white paper. https://ethereum.org/en/whitepaper/, 2013.

      5 5. M. Castro and B. Liskov. Practical byzantine fault tolerance. In Proceedings of the third symposium on Operating systems design and implementation, OSDI ’99, pages 173–186, Berkeley, CA, USA, 1999. USENIX Association.

      6 6. Channel Insider. Unplanned it outages cost more than $5,000 per minute: Report. http://www.channelinsider.com/c/a/Spotlight/Unplanned-IT-Outages-Cost-More-than-5000-per-Minute-Report-105393/, May 2011.

      7 7. J. Clark. The price of data center availability, October 2011. http://www.data-centerjournal.com/design/the-price-of-data-center-availability/.

      8 8. S. King and S. Nadal. Ppcoin: Peer-to-peer crypto-currency with proof-of-stake. https://www.peercoin.net/assets/paper/peercoin-paper.pdf, 2008.

      9 9. L. Lamport. Paxos made simple. ACM SIGACT News (Distributed Computing Column), 32(4):18–25, December 2001.

      10 10. L. Lamport. Fast paxos. Distributed Computing, 19(2):79–193, 2006.

      11 11. L. Lamport, R. Shostak, and M. Pease. The byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4:382–401, 1982.

      12 12. S. Nakamoto. Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf, 2008.

      13 13. T. Pisello and B. Quirk. How to quantify downtime, January 2004. http://www.networkworld.com/careers/2004/0105man.html.

      14 14. J. Poon and T. Dryja. The bitcoin lightning network: Scalable off-chain instant payments, 2016.

      15 15. Y. Saito and M. Shapiro. Optimistic replication. ACM Comput. Surv., 37(1):42– 81, Mar. 2005.

      16 16. M. Swan. Blockchain: Blueprint for a new economy. “O’Reilly Media, Inc.”, 2015.

      17 17. W. Wang, D. T. Hoang, P. Hu, Z. Xiong, D. Niyato, P. Wang, Y. Wen, and D. I. Kim. A survey on consensus mechanisms and mining strategy management in blockchain networks. IEEE Access, 7:22328–22370, 2019.

      18 18. W. Zhao. Fast paxos made easy: Theory and implementation. International Journal of Distributed Systems and Technologies (IJDST), 6(1):15–33, 2015.

      19 19. W. Zhao. Optimistic byzantine fault tolerance. International Journal of Parallel, Emergent and Distributed Systems, 31(3):254–267, 2016.

      20 20. W. Zhao, C. Jiang, H. Gao, S. Yang, and X. Luo. Blockchain-enabled cyber-physical systems: A review. IEEE Internet of Things Journal, 2020.

      21 21. W. Zhao, S. Yang, and X. Lou. Secure hierarchical processing and logging of sensing data and iot events with blockchain. In Proceedings of the 2020 International Conference on Blockchain Technology, pages 52–56. ACM, 2020.

      22 22. W. Zhao, S. Yang, and X. Luo. On consensus in public blockchains. In Proceedings of the 2019 International Conference on Blockchain Technology, pages 1–5, 2019.

СКАЧАТЬ