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Byzantine Collision-Fast Consensus Protocols

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Transactions on Computational Collective Intelligence XXXIII

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 11610))

Abstract

Atomic broadcast protocols are fundamental building blocks used in the construction of many reliable distributed systems. Atomic broadcast and consensus are equivalent problems, but the inefficiency of consensus-based atomic broadcast protocols in the presence of collisions (concurrent proposals) harms their adoption in the implementation of reliable systems, as the ones based on state machine replication. In the traditional consensus protocols, proposals that are not decided in some instance of consensus (commands not delivered) must be re-proposed in a new instance, delaying their execution. Moreover, whether different values (commands) are proposed in the same instance (leading to a collision), some of its phases must be restarted, also delaying the execution of these commands involved in the collision. The CFABCast (Collision-Fast Atomic Broadcast) algorithm uses m-consensus to decide and deliver multiple values in the same instance. However, CFABCast is not byzantine fault-tolerant, a requirement for many systems. Our first contribution is a modified version of CFABCast to handle byzantine failures. Unfortunately, the resulting protocol is not collision-fast due to the possibility of malicious failures. In fact, our second contribution is to prove that there are no byzantine collision-fast algorithms in an asynchronous model as traditionally extended to solve consensus. Finally, our third contribution is a byzantine collision-fast algorithm that bypasses the stated impossibility by means of a USIG (Unique Sequential Identifier Generator) trusted component.

This study was financed in part by the Coordenaição de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, PVE CAPES 88881.062190/2014-01.

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References

  1. Abd-El-Malek, M., Ganger, G., Goodson, G., Reiter, M., Wylie, J.: Fault-scalable Byzantine fault-tolerant services. In: Proceedings of the ACM Symposium on Operating Systems Principles (2005)

    Google Scholar 

  2. Abe, K., Ueda, T., Shikano, M., Ishibashi, H., Matsuura, T.: Toward fault-tolerant P2P systems: constructing a stable virtual peer from multiple unstable peers. In: 2009 First International Conference on Advances in P2P Systems, pp. 104–110 (2009)

    Google Scholar 

  3. Abraham, I., Malkhi, D., Nayak, K., Ren, L., Spiegelman, A.: Solida: a blockchain protocol based on reconfigurable byzantine consensus. In: Proceedings of the 21st International Conference on Principles of Distributed Systems (2017)

    Google Scholar 

  4. Alchieri, E.A.P., Bessani, A.N., da Silva Fraga, J., Greve, F.: Byzantine consensus with unknown participants. In: Baker, T.P., Bui, A., Tixeuil, S. (eds.) OPODIS 2008. LNCS, vol. 5401, pp. 22–40. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-92221-6_4

    Chapter  Google Scholar 

  5. Alchieri, E.A.P., Bessani, A., Greve, F., da Silva Fraga, J.: Knowledge connectivity requirements for solving byzantine consensus with unknown participants. IEEE Trans. Dependable Secur. Comput. 15(2), 246–259 (2018). https://doi.org/10.1109/TDSC.2016.2548460

    Article  Google Scholar 

  6. Benedictis, A.D., Rak, M., Villano, U.: Slas for cloud applications: agreement protocol and rest-based implementation. Int. J. Grid Util. Comput. 8(2), 120–132 (2017). https://doi.org/10.1504/IJGUC.2017.085910

    Article  Google Scholar 

  7. Birman, K., Chockler, G., van Renesse, R.: Toward a cloud computing research agenda. SIGACT News 40(2), 68–80 (2009). https://doi.org/10.1145/1556154.1556172

    Article  Google Scholar 

  8. Burrows, M.: The chubby lock service for loosely-coupled distributed systems (2006)

    Google Scholar 

  9. Cachin, C., Vukolic, M.: Blockchain consensus protocols in the wild. CoRR abs/1707.01873 (2017), http://arxiv.org/abs/1707.01873

  10. Calder, B., et al.: Windows azure storage: a highly available cloud storage service with strong consistency. In: Proceedings of the ACM Symposium on Operating Systems Principles (2011)

    Google Scholar 

  11. Castro, M., Liskov, B.: Practical byzantine fault tolerance. In: Proceedings of the 3rd Symposium on Operating Systems Design and Implementation, OSDI 1999, pp. 173–186. USENIX Association (1999)

    Google Scholar 

  12. Castro, M., Liskov, B.: Practical Byzantine fault-tolerance and proactive recovery. ACM Trans. Comput. Syst. 20(4), 398–461 (2002)

    Article  Google Scholar 

  13. Chandra, T.D., Hadzilacos, V., Toueg, S.: The weakest failure detector for solving consensus. J. ACM 43(4), 685–722 (1996). https://doi.org/10.1145/234533.234549

    Article  MathSciNet  MATH  Google Scholar 

  14. Chandra, T.D., Toueg, S.: Unreliable failure detectors for reliable distributed systems. J. ACM 43, 225–267 (1995)

    Article  MathSciNet  Google Scholar 

  15. Chun, B.G., Maniatis, P., Shenker, S., Kubiatowicz, J.: Attested append-only memory: making adversaries stick to their word. In: Proceedings of Twenty-First ACM SIGOPS Symposium on Operating Systems Principles, SOSP 2007, pp. 189–204. ACM, New York (2007). https://doi.org/10.1145/1294261.1294280

  16. Corbett, J., et al.: Spanner: Google’s globally-distributed database. In: Proceedings of the USENIX Symposium on Operating Systems Design and Implementation (2012)

    Google Scholar 

  17. Correia, M., Neves, N.F., Verissimo, P.: How to tolerate half less one byzantine nodes in practical distributed systems. In: Proceedings of the 23rd IEEE International Symposium on Reliable Distributed Systems, SRDS 2004, pp. 174–183. IEEE Computer Society, Washington, DC (2004)

    Google Scholar 

  18. Correia, M., Neves, N.F., Veríssimo, P.: From consensus to atomic broadcast: time-free Byzantine-resistant protocols without signatures. Comput. J. 49(1), 82–96 (2006)

    Article  Google Scholar 

  19. Cowling, J., Myers, D., Liskov, B., Rodrigues, R., Shrira, L.: HQ-replication: a hybrid quorum protocol for Byzantine fault tolerance. In: Proceedings of the USENIX Symposium on Operating Systems Design and Implementation, November 2006

    Google Scholar 

  20. DeCandia, G., et al.: Dynamo: Amazon’s highly available key-value store. In: Proceedings of Twenty-First ACM SIGOPS Symposium on Operating Systems Principles - SOSP 2007. ACM Press (2007). https://doi.org/10.1145/1294261.1294281

  21. Du, J., Sciascia, D., Elnikety, S., Zwaenepoel, W., Pedone, F.: Clock-RSM: low-latency inter-datacenter state machine replication using loosely synchronized physical clocks. In: 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2014, Atlanta, GA, USA, 23–26 June 2014, pp. 343–354 (2014). https://doi.org/10.1109/DSN.2014.42

  22. Dwork, C., Lynch, N., Stockmeyer, L.: Consensus in the presence of partial synchrony. J. ACM 35(2), 288–323 (1988). http://doi.acm.org/10.1145/42282.42283

  23. Eyal, I., Gencer, A.E., Sirer, E.G., Renesse, R.V.: Bitcoin-NG: a scalable blockchain protocol. In: 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2016), pp. 45–59. USENIX Association, Santa Clara (2016). https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/eyal

  24. Fischer, M.J., Lynch, N.A., Paterson, M.S.: Impossibility of distributed consensus with one faulty process (1985)

    Google Scholar 

  25. Galera Cluster: Minimizing downtime and maximizing elasticity with Galera Cluster for MySQL (2018). http://galeracluster.com/products/#white-papers-case-studies

  26. Gilad, Y., Hemo, R., Micali, S., Vlachos, G., Zeldovich, N.: Algorand: scaling byzantine agreements for cryptocurrencies. In: Proceedings of the 26th Symposium on Operating Systems Principles, SOSP 2017, pp. 51–68. ACM, New York (2017)

    Google Scholar 

  27. Hunt, P., Konar, M., Junqueira, F., Reed, B.: Zookeeper: wait-free coordination for Internet-scale services. In: Proceedings of the USENIX Annual Technical Conference (2010)

    Google Scholar 

  28. Kotla, R., Alvisi, L., Dahlin, M., Clement, A., Wong, E.: Zyzzyva: speculative Byzantine fault tolerance. ACM Trans. Comput. Syst. 27(4), 7:1–7:39 (2009)

    Google Scholar 

  29. Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21(7), 558–565 (1978). https://doi.org/10.1145/359545.359563

    Article  MATH  Google Scholar 

  30. Lamport, L.: The part-time parliament. ACM Trans. Comput. Syst. 16(2), 133–169 (1998)

    Article  Google Scholar 

  31. Lamport, L.: Generalized consensus and Paxos (2005)

    Google Scholar 

  32. Lamport, L.: Fast Paxos. Distrib. Comput. 19(2), 79–103 (2006). https://doi.org/10.1007/s00446-006-0005-x

    Article  MATH  Google Scholar 

  33. Lamport, L.: Lower bounds for asynchronous consensus. Distrib. Comput. 19(2), 104–125 (2006). https://doi.org/10.1007/s00446-006-0155-x

    Article  MATH  Google Scholar 

  34. Lamport, L., Shostak, R., Pease, M.: The byzantine generals problem. ACM Trans. Program. Lang. Syst. 4(3), 382–401 (1982). https://doi.org/10.1145/357172.357176

    Article  MATH  Google Scholar 

  35. Lampson, B.W.: How to build a highly available system using consensus. In: Babaoğlu, Ö., Marzullo, K. (eds.) WDAG 1996. LNCS, vol. 1151, pp. 1–17. Springer, Heidelberg (1996). https://doi.org/10.1007/3-540-61769-8_1

    Chapter  Google Scholar 

  36. Li, B., He, Y., Xu, K.: Distributed metadata management scheme in cloud computing. In: 2011 6th International Conference on Pervasive Computing and Applications, pp. 32–38, October 2011. https://doi.org/10.1109/ICPCA.2011.6106475

  37. Lin, S.-D., Lian, Q., Chen, M., Zhang, Z.: A practical distributed mutual exclusion protocol in dynamic peer-to-peer systems. In: Voelker, G.M., Shenker, S. (eds.) IPTPS 2004. LNCS, vol. 3279, pp. 11–21. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-30183-7_2

    Chapter  Google Scholar 

  38. Liu, Y., Ozera, K., Matsuo, K., Barolli, L.: An intelligent approach for qualified voting in P2P mobile collaborative team: a comparison study for two fuzzy-based systems. Int. J. Space Based Situated Comput. 7(4), 207–216 (2017). https://doi.org/10.1504/IJSSC.2017.089882

    Article  Google Scholar 

  39. Mao, Y., Junqueira, F.P., Marzullo, K.: Mencius: building efficient replicated state machines for WANs. In: Proceedings of the 8th USENIX Conference on Operating Systems Design and Implementation, OSDI 2008pp. 369–384. USENIX Association, Berkeley (2008)

    Google Scholar 

  40. Martin, J.P., Alvisi, L.: Fast byzantine consensus. IEEE Trans. Dependable Secur. Comput. 3(3), 202–215 (2006). https://doi.org/10.1109/TDSC.2006.35

    Article  Google Scholar 

  41. Messina, F., Pappalardo, G., Santoro, C., Rosaci, D., Sarné, G.M.L.: A multi-agent protocol for service level agreement negotiation in cloud federations. Int. J. Grid Util. Comput. 7(2), 101–112 (2016). https://doi.org/10.1504/IJGUC.2016.077488

    Article  Google Scholar 

  42. MySql Group Replication: Chap. 17 group replication (2018). https://dev.mysql.com/doc/refman/5.7/en/group-replication.html

  43. Nakagawa, T., Hayashibara, N.: Resource management for raft consensus protocol. Int. J. Space Based Situated Comput. 8(2), 80–87 (2018). https://doi.org/10.1504/IJSSC.2018.094467

    Article  Google Scholar 

  44. Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: A read-write abortion protocol to prevent illegal information flow in role-based access control systems. Int. J. Space Based Situated Comput. 6(1), 43–53 (2016). https://doi.org/10.1504/IJSSC.2016.076564

    Article  Google Scholar 

  45. Netto, H.V., Lung, L.C., Correia, M., Luiz, A.F., de Souza, L.M.S.: State machine replication in containers managed by kubernetes. J. Syst. Archit. 73, 53–59 (2017). https://doi.org/10.1016/j.sysarc.2016.12.007. Special Issue on Reliable Software Technologies for Dependable Distributed Systems

    Article  Google Scholar 

  46. Noor, T.H., Sheng, Q.Z.: Trust as a service: a framework for trust management in cloud environments. In: Bouguettaya, A., Hauswirth, M., Liu, L. (eds.) WISE 2011. LNCS, vol. 6997, pp. 314–321. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24434-6_27

    Chapter  Google Scholar 

  47. Ongaro, D., Ousterhout, J.: In search of an understandable consensus algorithm. In: USENIX Annual Technical Conference, pp. 305–320 (2014)

    Google Scholar 

  48. Pass, R., Shi, E.: Hybrid consensus: efficient consensus in the permissionless model. IACR Cryptology ePrint Archive 2016, 917 (2016)

    Google Scholar 

  49. Saramago, R., Alchieri, E.A.P., Rezende, T.F., Camargos, L.: On the impossibility of byzantine collision-fast atomic broadcast. In: 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA). pp. 414–421, May 2018. https://doi.org/10.1109/AINA.2018.00069

  50. Schmidt, R., Camargos, L., Pedone, F.: On collision-fast atomic broadcast. Technical report, SemanticScholar (2007)

    Google Scholar 

  51. Schmidt, R., Camargos, L., Pedone, F.: Collision-fast atomic broadcast. In: Proceedings of the 2014 IEEE 28th International Conferene on Advanced Information Networking and Applications, AINA 2014, pp. 1065–1072. IEEE Computer Society, Washington, DC (2014)

    Google Scholar 

  52. Schütt, T., Schintke, F., Reinefeld, A.: Scalaris: Reliable transactional P2P key/value store. In: Proceedings of the 7th ACM SIGPLAN Workshop on ERLANG, ERLANG 2008, New York, NY, USA, pp. 41–48 (2008)

    Google Scholar 

  53. Valduriez, P., Pacitti, E.: Data management in large-scale P2P systems. In: Daydé, M., Dongarra, J., Hernández, V., Palma, J.M.L.M. (eds.) VECPAR 2004. LNCS, vol. 3402, pp. 104–118. Springer, Heidelberg (2005). https://doi.org/10.1007/11403937_9

    Chapter  Google Scholar 

  54. Veronese, G.S., Correia, M., Bessani, A.N., Lung, L.C., Verissimo, P.: Efficient byzantine fault-tolerance. IEEE Trans. Comput. 62(1), 16–30 (2013). https://doi.org/10.1109/TC.2011.221

    Article  MathSciNet  MATH  Google Scholar 

  55. Vukolić, M.: The quest for scalable blockchain fabric: proof-of-work vs. BFT replication. In: Camenisch, J., Kesdoğan, D. (eds.) iNetSec 2015. LNCS, vol. 9591, pp. 112–125. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39028-4_9

    Chapter  Google Scholar 

  56. Weiss, S., Urso, P., Molli, P.: Logoot: a scalable optimistic replication algorithm for collaborative editing on P2P networks. In: 2009 29th IEEE International Conference on Distributed Computing Systems, pp. 404–412, June 2009

    Google Scholar 

  57. Zhao, W., Melliar-Smith, P.M., Moser, L.E.: Fault tolerance middleware for cloud computing. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 67–74, July 2010. https://doi.org/10.1109/CLOUD.2010.26

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Saramago, R., Alchieri, E., Rezende, T., Camargos, L. (2019). Byzantine Collision-Fast Consensus Protocols. In: Nguyen, N., Kowalczyk, R., Xhafa, F. (eds) Transactions on Computational Collective Intelligence XXXIII. Lecture Notes in Computer Science(), vol 11610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59540-4_6

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