Byzantine Approximate Agreement on Graphs

Authors Thomas Nowak , Joel Rybicki



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Author Details

Thomas Nowak
  • Université Paris-Sud, France
  • Centre National de la Recherche Scientifique, Paris, France
Joel Rybicki
  • Institute of Science and Technology Austria, Klosterneuburg, Austria

Acknowledgements

We thank the anonymous reviewers for their helpful comments and Janne H. Korhonen for many discussions on this work. We also wish to thank the participants of the Helsinki Workshop on Theory of Distributed Computing 2018 and the Metastability workshop in Mainz 2018 for discussions that lead to the problem of approximate agreement on graphs.

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Thomas Nowak and Joel Rybicki. Byzantine Approximate Agreement on Graphs. In 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 146, pp. 29:1-29:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.DISC.2019.29

Abstract

Consider a distributed system with n processors out of which f can be Byzantine faulty. In the approximate agreement task, each processor i receives an input value x_i and has to decide on an output value y_i such that 
1) the output values are in the convex hull of the non-faulty processors' input values, 
2) the output values are within distance d of each other. 
 Classically, the values are assumed to be from an m-dimensional Euclidean space, where m >= 1.
In this work, we study the task in a discrete setting, where input values with some structure expressible as a graph. Namely, the input values are vertices of a finite graph G and the goal is to output vertices that are within distance d of each other in G, but still remain in the graph-induced convex hull of the input values. For d=0, the task reduces to consensus and cannot be solved with a deterministic algorithm in an asynchronous system even with a single crash fault. For any d >= 1, we show that the task is solvable in asynchronous systems when G is chordal and n > (omega+1)f, where omega is the clique number of G. In addition, we give the first Byzantine-tolerant algorithm for a variant of lattice agreement. For synchronous systems, we show tight resilience bounds for the exact variants of these and related tasks over a large class of combinatorial structures.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • consensus
  • approximate agreement
  • Byzantine faults
  • chordal graphs
  • lattice agreement

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References

  1. Ittai Abraham, Yonatan Amit, and Danny Dolev. Optimal Resilience Asynchronous Approximate Agreement. In Proc. International Conference on Principles of Distributed Systems (OPODIS 2015), pages 229-239, 2005. URL: https://doi.org/10.1007/11516798_17.
  2. Hagit Attiya and Arie Fouren. Adaptive and efficient algorithms for lattice agreement and renaming. SIAM Journal on Computing, 31(2):642-664, 2001. Google Scholar
  3. Hagit Attiya, Maurice Herlihy, and Ophir Rachman. Atomic snapshots using lattice agreement. Distributed Computing, 8(3):121-132, 1995. Google Scholar
  4. Rommel M Barbosa, Erika M. M. Coelho, Mitre C. Dourado, Dieter Rautenbach, and Jayme L. Szwarcfiter. On the Carathéodory number for the convexity of paths of order three. SIAM Journal on Discrete Mathematics, 26(3):929-939, 2012. Google Scholar
  5. Anne Berry and Romain Pogorelcnik. A simple algorithm to generate the minimal separators and the maximal cliques of a chordal graph. Information Processing Letters, 111:508-511, 2011. Google Scholar
  6. Martin Biely, Peter Robinson, and Ulrich Schmid. Easy impossibility proofs for k-set agreement in message passing systems. In Proc. International Conference on Principles of Distributed Systems (OPODIS 2011), pages 299-312. Springer, 2011. Google Scholar
  7. Jean R. S. Blair and Barry Peyton. An Introduction to Chordal Graphs and Clique Trees. In Alan George, John R. Gilbert, and Joseph W. H. Liu, editors, Graph Theory and Sparse Matrix Computation, pages 1-29. Springer, Heidelberg, 1993. Google Scholar
  8. Soma Chaudhuri. More choices allow more faults: Set consensus problems in totally asynchronous systems. Information and Computation, 105(1):132-158, 1993. Google Scholar
  9. Roberto De Prisco, Dahlia Malkhi, and Michael Reiter. On k-set consensus problems in asynchronous systems. IEEE Transactions on Parallel and Distributed Systems, 12(1):7-21, 2001. Google Scholar
  10. Reinhard Diestel. Graph Theory. Springer, Heidelberg, 4th edition, 2010. Google Scholar
  11. Brenda L. Dietrich. Matroids and antimatroids - a survey. Discrete Mathematics, 78(3):223-237, 1989. Google Scholar
  12. Gabriel Andrew Dirac. On rigid circuit graphs. In Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg, volume 25, pages 71-76. Springer, 1961. Google Scholar
  13. Danny Dolev, Matthias Függer, Christoph Lenzen, and Ulrich Schmid. Fault-tolerant algorithms for tick-generation in asynchronous logic. Journal of the ACM, 61(5):30:1-30:74, 2014. URL: https://doi.org/10.1145/2560561.
  14. Danny Dolev, Nancy A. Lynch, Shlomit S. Pinter, Eugene W. Stark, and William E. Weihl. Reaching Approximate Agreement in the Presence of Faults. Journal of the ACM, 33(3):499-516, May 1986. URL: https://doi.org/10.1145/5925.5931.
  15. Danny Dolev and Rüdiger Reischuk. Bounds on information exchange for Byzantine agreement. Journal of the ACM, 32(1):191-204, 1985. URL: https://doi.org/10.1145/2455.214112.
  16. Shlomi Dolev and Jennifer L. Welch. Self-stabilizing clock synchronization in the presence of Byzantine faults. Journal of the ACM, 51(5):780-799, 2004. URL: https://doi.org/10.1145/1017460.1017463.
  17. Mitre C. Dourado, Dieter Rautenbach, Vinícius Fernandes dos Santos, Philipp M. Schäfer, and Jayme L. Szwarcfiter. On the Carathéodory number of interval and graph convexities. Theoretical Computer Science, 510:127-135, 2013. URL: https://doi.org/10.1016/j.tcs.2013.09.004.
  18. Pierre Duchet. Convexity in combinatorial structures. In Proc. Winter School on Abstract Analysis, pages 261-293. Circolo Matematico di Palermo, 1987. Google Scholar
  19. Pierre Duchet. Convex sets in graphs, II. Minimal path convexity. Journal of Combinatorial Theory, Series B, 44(3):307-316, 1988. URL: https://doi.org/10.1016/0095-8956(88)90039-1.
  20. Jürgen Eckhoff. Helly, Radon, and Carathéodory type theorems. In Handbook of Convex Geometry, Part A, pages 389-448. Elsevier Science Publishers B.V, 1993. Google Scholar
  21. Paul H. Edelman and Robert E. Jamison. The theory of convex geometries. Geometriae Dedicata, 19(3):247-270, 1985. URL: https://doi.org/10.1007/BF00149365.
  22. Paul H. Edelman and Michael E. Saks. Combinatorial representation and convex dimension of convex geometries. Order, 5(1):23-32, 1988. URL: https://doi.org/10.1007/BF00143895.
  23. Jose M. Faleiro, Sriram Rajamani, Kaushik Rajan, G. Ramalingam, and Kapil Vaswani. Generalized lattice agreement. In Proc. ACM Symposium on Principles of Distributed Computing (PODC 2012), pages 125-134. ACM, 2012. URL: https://doi.org/10.1145/2332432.2332458.
  24. M. Farber and R. E. Jamison. Convexity in graphs and hypergraphs. SIAM Journal on Algebraic Discrete Methods, 7(3):433-444, 1986. Google Scholar
  25. Martin Farber and Robert E. Jamison. On local convexity in graphs. Discrete Mathematics, 66(3):231-247, 1987. URL: https://doi.org/10.1016/0012-365X(87)90099-9.
  26. Alan David Fekete. Asymptotically optimal algorithms for approximate agreement. Distributed Computing, 4(1):9-29, 1990. Google Scholar
  27. Alan David Fekete. Asynchronous approximate agreement. Information and Computation, 115(1):95-124, 1994. Google Scholar
  28. Michael J. Fischer, Nancy A. Lynch, and Michael S. Paterson. Impossibility of distributed consensus with one faulty process. Journal of the ACM, 32(2):374-382, 1985. URL: https://doi.org/10.1145/3149.214121.
  29. Eli Gafni and Petr Kuznetsov. N-consensus is the second strongest object for N+1 processes. In Proc. International Conference on Principles of Distributed Systems (OPODIS 2007), pages 260-273. Springer, Heidelberg, 2007. Google Scholar
  30. Fănică Gavril. Algorithms for minimum coloring, maximum clique, minimum covering by cliques, and maximum independent set of a chordal graph. SIAM Journal on Computing, 1(2):180-187, 1972. Google Scholar
  31. Maurice Herlihy, Dmitry Kozlov, and Sergio Rajsbaum. Distributed Computing Through Combinatorial Topology. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1st edition, 2013. Google Scholar
  32. Maurice Herlihy and Sergio Rajsbaum. A classification of wait-free loop agreement tasks. Theoretical Computer Science, 291(1):55-77, 2003. Google Scholar
  33. Maurice Herlihy, Sergio Rajsbaum, and Mark R. Tuttle. Unifying synchronous and asynchronous message-passing models. In Proc. ACM Symposium on Principles of Distributed Computing (PODC 1998), pages 133-142. ACM, 1998. Google Scholar
  34. Robert E. Jamison and Richard Nowakowski. A Helly theorem for convexity in graphs. Discrete Mathematics, 51(1):35-39, 1984. URL: https://doi.org/10.1016/0012-365X(84)90021-9.
  35. Robert E Jamison-Waldner. A perspective on abstract convexity: classifying alignments by varieties. Convexity and Related Combinatorial Geometry, New York, 1982. Google Scholar
  36. David Kay and Eugene W Womble. Axiomatic convexity theory and relationships between the Carathéodory, Helly, and Radon numbers. Pacific Journal of Mathematics, 38(2):471-485, 1971. Google Scholar
  37. Christian Konrad and Viktor Zamaraev. Brief Announcement: Distributed Minimum Vertex Coloring and Maximum Independent Set in Chordal Graphs. In Proc. ACM Symposium on Principles of Distributed Computing (PODC 2018), pages 159-161, New York, NY, USA, 2018. ACM. URL: https://doi.org/10.1145/3212734.3212787.
  38. Bernhard Korte and László Lovász. Greedoids - A Structural Framework for the Greedy Algorithm. In Progress in Combinatorial Optimization, pages 221-243. Academic Press, 1984. URL: https://doi.org/10.1016/B978-0-12-566780-7.50019-2.
  39. Bernhard Korte, László Lovász, and Rainer Schrader. Greedoids, volume 4. Springer Science & Business Media, 2012. Google Scholar
  40. Steffen L. Lauritzen. Graphical models, volume 17. Clarendon Press, 1996. Google Scholar
  41. Christoph Lenzen and Joel Rybicki. Near-optimal self-stabilising counting and firing squads. Distributed Computing, 2018. URL: https://doi.org/10.1007/s00446-018-0342-6.
  42. Christoph Lenzen and Joel Rybicki. Self-Stabilising Byzantine Clock Synchronisation is Almost as Easy as Consensus. Journal of the ACM, 2019. To appear. Google Scholar
  43. Xingwu Liu, Zhiwei Xu, and Jianzhong Pan. Classifying rendezvous tasks of arbitrary dimension. Theoretical Computer Science, 410(21):2162-2173, 2009. URL: https://doi.org/10.1016/j.tcs.2009.01.033.
  44. László Lovăsz and Michael Saks. Communication complexity and combinatorial lattice theory. Journal of Computer and System Sciences, 47(2):322-349, 1993. Google Scholar
  45. Tze-Heng Ma and Jeremy P. Spinrad. Cycle-free partial orders and chordal comparability graphs. Order, 8(1):49-61, March 1991. URL: https://doi.org/10.1007/BF00385814.
  46. Hammurabi Mendes and Maurice Herlihy. Multidimensional approximate agreement in Byzantine asynchronous systems. Proc. Annual ACM symposium on Symposium on Theory of Computing (STOC 2013), page 391, 2013. URL: https://doi.org/10.1145/2488608.2488657.
  47. Hammurabi Mendes, Maurice Herlihy, Nitin Vaidya, and Vijay K. Garg. Multidimensional agreement in Byzantine systems. Distributed Computing, 28:423-441, 2015. Google Scholar
  48. Morten H. Nielsen and Ortrud R. Oellermann. Steiner trees and convex geometries. SIAM Journal on Discrete Mathematics, 23(2):680-693, 2009. Google Scholar
  49. Marshall C. Pease, Robert E. Shostak, and Leslie Lamport. Reaching agreement in the presence of faults. Journal of the ACM, 27(2):228-234, 1980. URL: https://doi.org/10.1145/322186.322188.
  50. Ignacio M. Pelayo. Geodesic Convexity in Graphs. Springer, 2013. URL: https://doi.org/10.1007/978-1-4614-8699-2.
  51. Paul Poncet. Convexities on ordered structures have their Krein-Milman theorem. Journal of Convex Analysis, 21(1):89-120, 2014. Google Scholar
  52. Donald J. Rose. Triangulated graphs and the elimination process. Journal of Mathematical Analysis and Applications, 32(3):597-609, 1970. Google Scholar
  53. Donald J. Rose, R. Endre Tarjan, and George S. Lueker. Algorithmic aspects of vertex elimination on graphs. SIAM Journal on computing, 5(2):266-283, 1976. Google Scholar
  54. Nitin H. Vaidya and Vijay K. Garg. Byzantine vector consensus in complete graphs. In Proc. ACM Symposium on Principles of Distributed Computing (PODC 2013), pages 65-73, 2013. Google Scholar
  55. Marcel LJ van De Vel. Theory of convex structures, volume 50. Elsevier, 1993. Google Scholar
  56. Lieven Vandenberghe and Martin S Andersen. Chordal graphs and semidefinite optimization. Foundations and Trends in Optimization, 1(4):241-433, 2015. Google Scholar
  57. Jennifer Lundelius Welch and Nancy Lynch. A new fault-tolerant algorithm for clock synchronization. Information and Computation, 77(1):1-36, 1988. Google Scholar
  58. Xiong Zheng, Changyong Hu, and Vijay K. Garg. Lattice Agreement in Message Passing Systems. In Proc. International Symposium on Distributed Computing (DISC 2018), volume 121 of Leibniz International Proceedings in Informatics (LIPIcs), pages 41:1-41:17, Dagstuhl, Germany, 2018. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. URL: https://doi.org/10.4230/LIPIcs.DISC.2018.41.
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