Capacity of Agreement with Finite Link Capacity

In this paper, we consider the problem of maximizing the throughput of Byzantine agreement, when communication links have finite capacity. Byzantine agreement is a classical problem in distributed computing, with initial solutions presented in the seminal work of Pease, Shostak and Lamport. In existing literature, the communication links are implicitly assumed to have infinite capacity. The problem changes significantly when the capacity of links is finite. The notion of throughput here is similar to that used in the networking/communications literature on unicast or multicast traffic. We identify necessary conditions of achievable agreement throughputs. We propose an algorithm structure for achieving agreement capacity in general networks. We also introduce capacity achieving algorithms for two classes of networks: (i) symmetric networks with n ≥ 4 nodes and up to t < n/3 failures; (ii) arbitrary four-node networks with at most 1 failure.

[1]  Guanfeng Liang,et al.  Capacity of Byzantine Agreement: Complete Characterization of Four-Node Networks ∗ , 2010 .

[2]  Lang Tong,et al.  Nonlinear network coding is necessary to combat general Byzantine attacks , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[3]  Tal Mizrahi,et al.  Continuous Consensus with Failures and Recoveries , 2008, DISC.

[4]  Tal Mizrahi,et al.  Continuous consensus with ambiguous failures , 2008, Theor. Comput. Sci..

[5]  Robert Griesemer,et al.  Paxos made live: an engineering perspective , 2007, PODC '07.

[6]  Tracey Ho,et al.  Resilient network coding in the presence of Byzantine adversaries , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[7]  Christina Fragouli,et al.  On Feedback for Network Coding , 2007, 2007 41st Annual Conference on Information Sciences and Systems.

[8]  Tal Mizrahi,et al.  Continuous consensus via common knowledge , 2005, Distributed Computing.

[9]  Tracey Ho,et al.  Byzantine modification detection in multicast networks using randomized network coding , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[10]  Miguel Castro,et al.  Practical byzantine fault tolerance and proactive recovery , 2002, TOCS.

[11]  Roy Friedman,et al.  Distributed Agreement and Its Relation with Error-Correcting Codes , 2002, DISC.

[12]  R. Koetter,et al.  An algebraic approach to network coding , 2001, Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252).

[13]  Leslie Lamport,et al.  The part-time parliament , 1998, TOCS.

[14]  Joseph Y. Halpern,et al.  The Failure Discovery problem , 1993, Mathematical systems theory.

[15]  Joseph Y. Halpern,et al.  Message-optimal protocols for Byzantine Agreement , 1993, Mathematical systems theory.

[16]  Vassos Hadzilacos,et al.  On the message complexity of binary byzantine agreement under crash failures , 1992, Distributed Computing.

[17]  Michael O. Rabin,et al.  Efficient dispersal of information for security, load balancing, and fault tolerance , 1989, JACM.

[18]  Eric C. Cooper Replicated distributed programs , 1985, SOSP '85.

[19]  J. T. Sims,et al.  The Byzantine Generals Problem , 1982, TOPL.

[20]  Leslie Lamport,et al.  Reaching Agreement in the Presence of Faults , 1980, JACM.

[21]  GERNOT METZE,et al.  On the Connection Assignment Problem of Diagnosable Systems , 1967, IEEE Trans. Electron. Comput..

[22]  T. Ho,et al.  On Linear Network Coding , 2010 .

[23]  Nitin H. Vaidya,et al.  Secure Capacity of Wireless Broadcast Networks , 2009 .

[24]  R. Yeung,et al.  NETWORK ERROR CORRECTION, PART II: LOWER BOUNDS , 2006 .

[25]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[26]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.