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Fast byzantine agreement in dynamic networks

Published:22 July 2013Publication History

ABSTRACT

We study Byzantine agreement in dynamic networks where topology can change from round to round and nodes can also experience heavy churn (i.e., nodes can join and leave the network continuously over time). Our main contributions are randomized distributed algorithms that achieve almost-everywhere Byzantine agreement with high probability even under a large number of adaptively chosen Byzantine nodes and continuous adversarial churn in a number of rounds that is polylogarithmic in n (where n is the stable network size). We show that our algorithms are essentially optimal (up to polylogarithmic factors) with respect to the amount of Byzantine nodes and churn rate that they can tolerate by showing a lower bound. In particular, we present the following results:

1. An O(log3 n) round randomized algorithmto achieve almost everywhere Byzantine agreement with high probability under a presence of up to O(√n/polylog(n)) Byzantine nodes and up to a churn of O(√n/polylog(n)) nodes per round. We assume that the Byzantine nodes have knowledge about the entire state of network at every round (including random choices made by all the nodes) and can behave arbitrarily. We also assume that an adversary controls the churn - it has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power (but is oblivious to the topology changes from round to round). Our algorithm requires only polylogarithmic in n bits to be processed and sent (per round) by each node.

2. We also present an O(log3 n) round randomized algorithm that has same guarantees as the above algorithm, but works even when the connectivity of the network is controlled by an adaptive adversary (that can choose the topology based on the current states of the nodes). However, this algorithm requires up to polynomial in n bits to be processed and sent (per round) by each node.

3. We show that the above bounds are essentially the best possible, if one wants fast (i.e., polylogarithmic run time) algorithms, by showing that any (randomized) algorithm to achieve agreement in a dynamic network controlled by an adversary that can churn up to Θ(√n log n) nodes per round should take at least a polynomial number of rounds.

Our algorithms are the first-known, fully distributed, Byzantine agreement algorithms in highly dynamic networks. We view our results as a step towards understanding the possibilities and limitations of highly dynamic networks that are subject to malicious behavior by a large number of nodes.

References

  1. James Aspnes. Lower bounds for distributed coin-flipping and randomized consensus. In STOC '97, p. 559--568, New York, NY, USA, 1997. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Hagit Attiya and Jennifer Welch. Distributed Computing: Fundamentals, Simulations and Advanced Topics (2nd edition). John Wiley Interscience, March 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. John Augustine, Gopal Pandurangan, and Peter Robinson. Fast Byzantine Agreement in Dynamic Networks. (to appear in arXiv), 2013.Google ScholarGoogle Scholar
  4. John Augustine, Gopal Pandurangan, Peter Robinson, and Eli Upfal. Towards robust and efficient computation in dynamic peer-to-peer networks. In ACM-SIAM, SODA 2012, p. 551--569. SIAM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Chen Avin, Michal Koucký, and Zvi Lotker. How to explore a fast-changing world (cover time of a simple random walk on evolving graphs). In ICALP, p. 121--132, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Baruch Awerbuch and Christian Scheideler. Towards a scalable and robust dht. Theory Comput. Syst., 45(2):234--260, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Amitabha Bagchi, Ankur Bhargava, Amitabh Chaudhary, David Eppstein, and Christian Scheideler. The effect of faults on network expansion. Theory Comput. Syst., 39(6):903--928, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Ziv Bar-Joseph and Michael Ben-Or. A tight lower bound for randomized synchronous consensus. In PODC '98, p. 193--199, New York, NY, USA, 1998. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Ben-Or and N. Linial. Collective coin flipping. In Silvio Micali, editor, Advances in Computing Research 5: Randomness and Computation, volume 5, p. 91--115. JAI Press, 1989.Google ScholarGoogle Scholar
  10. Piotr Berman and Juan A. Garay. Fast consensus in networks of bounded degree. Distributed Computing, 7(2):67--73, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Arnaud Casteigts, Paola Flocchini, Walter Quattrociocchi, and Nicola Santoro. Time-varying graphs and dynamic networks. CoRR, abs/1012.0009, 2010. Short version in ADHOC-NOW 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. A. Das Sarma, A. Molla, and G. Pandurangan. Fast distributed computation in dynamic networks via random walks. In DISC, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Benjamin Doerr, Leslie Ann Goldberg, Lorenz Minder, Thomas Sauerwald, and Christian Scheideler. Stabilizing consensus with the power of two choices. In SPAA, p. 149--158, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Danny Dolev and H. Raymond Strong. Authenticated algorithms for byzantine agreement. SIAM J. Comput., 12(4):656--666, 1983.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Cynthia Dwork, David Peleg, Nicholas Pippenger, and Eli Upfal. Fault tolerance in networks of bounded degree. SIAM J. Comput., 17(5):975--988, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Amos Fiat and Jared Saia. Censorship resistant peer-to-peer content addressable networks. In SODA, p. 94--103, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Michael J. Fischer and Nancy A. Lynch. A lower bound for the time to assure interactive consistency. Inf. Process. Lett., 14(4):183--186, 1982.Google ScholarGoogle ScholarCross RefCross Ref
  18. Kirsten Hildrum and John Kubiatowicz. Asymptotically efficient approaches to fault-tolerance in peer-to-peer networks. In DISC, volume 2848 of LNCS, p. 321--336. Springer, 2003.Google ScholarGoogle Scholar
  19. Bruce M. Kapron, David Kempe, Valerie King, Jared Saia, and Vishal Sanwalani. Fast asynchronous byzantine agreement and leader election with full information. ACM Transactions on Algorithms, 6(4), 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Valerie King and Jared Saia. Breaking the O(n2) bit barrier: scalable Byzantine agreement with an adaptive adversary. In PODC, p. 420--429, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Valerie King, Jared Saia, Vishal Sanwalani, and Erik Vee. Scalable leader election. In SODA, p. 990--999, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Valerie King, Jared Saia, Vishal Sanwalani, and Erik Vee. Towards secure and scalable computation in peer-to-peer networks. In FOCS, p. 87--98, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Fabian Kuhn, Nancy Lynch, and Rotem Oshman. Distributed computation in dynamic networks. In ACM STOC, p. 513--522, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Fabian Kuhn, Rotem Oshman, and Yoram Moses. Coordinated consensus in dynamic networks. In PODC, p. 1--10, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Fabian Kuhn, Stefan Schmid, and Roger Wattenhofer. Towards worst-case churn resistant peer-to-peer systems. Distributed Computing, 22(4):249--267, 2010.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. C. Law and K.-Y. Siu. Distributed construction of random expander networks. In INFOCOM 2003, volume 3, p. 2133--2143 vol.3, march-3 april 2003.Google ScholarGoogle ScholarCross RefCross Ref
  27. Nancy Lynch. Distributed Algorithms. Morgan Kaufman Publishers, Inc., San Francisco, USA, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Moni Naor and Udi Wieder. A simple fault tolerant distributed hash table. In IPTPS, p. 88--97, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  29. Regina O'Dell and Roger Wattenhofer. Information dissemination in highly dynamic graphs. In DIALM-POMC, p. 104--110, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Gopal Pandurangan, Prabhakar Raghavan, and Eli Upfal. Building low-diameter p2p networks. In FOCS, p. 492--499, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Gopal Pandurangan, Peter Robinson, and Amitabh Trehan. DEX: Self healing Expanders. Manuscript, 2013.Google ScholarGoogle Scholar
  32. Christian Scheideler. How to spread adversarial nodes?: rotate! In STOC, p. 704--713, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Christian Scheideler and Stefan Schmid. A distributed and oblivious heap. In Automata, Languages and Programming, volume 5556 of LNCS, p. 571--582. Springer, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Eli Upfal. Tolerating a linear number of faults in networks of bounded degree. Inf. Comput., 115(2):312--320, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      PODC '13: Proceedings of the 2013 ACM symposium on Principles of distributed computing
      July 2013
      422 pages
      ISBN:9781450320658
      DOI:10.1145/2484239

      Copyright © 2013 ACM

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      Publication History

      • Published: 22 July 2013

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      PODC '13 Paper Acceptance Rate37of145submissions,26%Overall Acceptance Rate740of2,477submissions,30%

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