Fast byzantine agreement in dynamic networks

Augustine, John; Pandurangan, Gopal; Robinson, Peter

doi:10.1145/2484239.2484275

Cited by 56 publications

(84 citation statements)

References 26 publications

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“…Its main contribution is an efficient and scalable randomized distributed algorithm (i.e., each node processes and sends only polylogarithmic messages per round, and local computation per node is also lightweight) that guarantees stable almosteverywhere agreement 1 with high probability even under very high adversarial churn rate (up to linear in n per round, where n is the network size) in a polylogarithmic number of rounds. The work of [21] presented an efficient distributed algorithm for Byzantine agreement that works despite the presence of Byzantine nodes and high adversarial churn. This algorithm could tolerate up to O( √ n/ polylog(n)) Byzantine nodes and up to O( √ n/ polylog(n) churn per round, took a polylogarithmic number of rounds, and was scalable.…”

Section: Introductionmentioning

confidence: 99%

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Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Augustine

Pandurangan

Robinson

et al. 2015

2015 IEEE 56th Annual Symposium on Foundations of Computer Science

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Section: Introductionmentioning

confidence: 99%

“…However, none of these works guarantee the maintenance of an expander under the more challenging situation of high continuous adversarial churn. This is a fundamental ingredient that is needed to enable the applicability of previous results ( [19], [21], [22], [59]) under a more realistic setting.…”

Section: Introductionmentioning

confidence: 99%

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Augustine

Pandurangan

Robinson

et al. 2015

2015 IEEE 56th Annual Symposium on Foundations of Computer Science

Self Cite

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“…(Our model is described in detail in Section 1.1, it is similar to the model considered in prior work, e.g., [6,4,5].) We consider a dynamic network as a sparse bounded degree expander graph whose topology -both nodes and edges -can change arbitrarily from round to round and is controlled by an adversary.…”

Section: Introductionmentioning

confidence: 99%

“…The main technical challenge that we have to overcome is designing and analyzing distributed algorithms with the presence of Byzantine nodes in networks where both nodes and edges can change by a large amount continuously in each round. The same challenge was present in solving the Byzantine agreement problem in such networks which was addressed in [4]. However, this does not directly solve the leader election problem, since the value that (most of) the honest nodes agree may be a value that was generated by a Byzantine node; using the agreement algorithm in a straightforward way does not give any guarantee that an honest node will be elected as leader.…”

Section: Introductionmentioning

confidence: 99%

“…Our storage and verification mechanism needs to store each lottery ticket in about √ n nodes, and to be scalable in terms of the number of messages generated, it can handle only about √ n nodes (each such node generates a ticket, thus overall there will be about n polylog(n) messages -anything significantly more than this will cause much more congestion). The second reason is that for solving Byzantine agreement, we use a majority rule to progress towards agreement [12,4]. This majority rule algorithm works as long as the number of Byzantine nodes are bounded by O( √ n).…”

Section: Introductionmentioning

confidence: 99%

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Fast Byzantine Leader Election in Dynamic Networks

Augustine

Pandurangan

Robinson

2015

Lecture Notes in Computer Science

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Abstract. We study the fundamental Byzantine leader election problem in dynamic networks where the 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). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an O(log 3 n) round algorithm that achieves Byzantine leader election under the presence of up to O(n 1/2−ε ) Byzantine nodes (for a small constant ε > 0) and a churn of up to O( √ n/ polylog(n)) nodes per round (where n is the stable network size). The algorithm elects a leader with probability at least 1 − n −Ω(1) and guarantees that it is an honest node with probability at least 1 − n −Ω(1) ; assuming the algorithm succeeds, the leader's identity will be known to a 1 − o(1) fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in n) time and requires nodes to send and receive messages of only polylogarithmic size per round. To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way. We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

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Discovery Through Gossip

Haeupler

Pandurangan

Peleg³

et al. 2016

Random Struct Algorithms

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We study randomized gossip‐based processes in dynamic networks that are motivated by information discovery in large‐scale distributed networks such as peer‐to‐peer and social networks. A well‐studied problem in peer‐to‐peer networks is resource discovery, where the goal for nodes (hosts with IP addresses) is to discover the IP addresses of all other hosts. Also, some of the recent work on self‐stabilization algorithms for P2P/overlay networks proceed via discovery of the complete network. In social networks, nodes (people) discover new nodes through exchanging contacts with their neighbors (friends). In both cases the discovery of new nodes changes the underlying network — new edges are added to the network — and the process continues in the changed network. Rigorously analyzing such dynamic (stochastic) processes in a continuously changing topology remains a challenging problem with obvious applications. This paper studies and analyzes two natural gossip‐based discovery processes. In the push discovery or triangulation process, each node repeatedly chooses two random neighbors and connects them (i.e., “pushes” their mutual information to each other). In the pull discovery process or the two‐hop walk, each node repeatedly requests or “pulls” a random contact from a random neighbor and connects itself to this two‐hop neighbor. Both processes are lightweight in the sense that the amortized work done per node is constant per round, local, and naturally robust due to the inherent randomized nature of gossip. Our main result is an almost‐tight analysis of the time taken for these two randomized processes to converge. We show that in any undirected n‐node graph both processes take O(nlog2n) rounds to connect every node to all other nodes with high probability, whereas Ω(nlogn) is a lower bound. We also study the two‐hop walk in directed graphs, and show that it takes O(n2logn) time with high probability, and that the worst‐case bound is tight for arbitrary directed graphs, whereas Ω(n2) is a lower bound for strongly connected directed graphs. A key technical challenge that we overcome in our work is the analysis of a randomized process that itself results in a constantly changing network leading to complicated dependencies in every round. We discuss implications of our results and their analysis to discovery problems in P2P networks as well as to evolution in social networks. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 48, 565–587, 2016

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Fast byzantine agreement in dynamic networks

Cited by 56 publications

References 26 publications

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Fast Byzantine Leader Election in Dynamic Networks

Discovery Through Gossip

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