A Time-Free Byzantine Failure Detector for Dynamic Networks

Greve, Fabíola; Lima, Murilo Santos de; Arantes, Luciana; Sens, Pierre

doi:10.1109/edcc.2012.28

Cited by 9 publications

(8 citation statements)

References 22 publications

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“…Byzantine fault detection in the context of asynchronous distributed systems. There have also been several works on Byzantine fault detection -see, e.g., [1], [29], [25], and [23]. Alvisi et al [1] consider the problem of fault detection in Byzantine quorum systems and design statistical methods to compute the current number of failures at any point of time.…”

Section: Other Related Workmentioning

confidence: 99%

“…Greve et al [23] design and analyze a powerful Byzantine failure detector that works in dynamic distributed systems, where both the number of processors and the topology of the communication graph can change from round to round. Their work does not assume any knowledge of n; however, their work does not solve the Byzantine counting problem either -no estimate about the global network size can be made during the execution of their algorithm.…”

Section: Other Related Workmentioning

confidence: 99%

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Byzantine-Resilient Counting in Networks

Chatterjee¹,

Pandurangan²,

Robinson³

2022

Preprint

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We present two distributed algorithms for the Byzantine counting problem, which is concerned with estimating the size of a network in the presence of a large number of Byzantine nodes.In an n-node network (n is unknown), our first algorithm, which is deterministic, finishes in O(log n) rounds and is time-optimal. This algorithm can tolerate up to O(n 1−γ ) arbitrarily (adversarially) placed Byzantine nodes for any arbitrarily small (but fixed) positive constant γ. It outputs a (fixed) constant factor estimate of log n that would be known to all but o(1) fraction of the good nodes. This algorithm works for any bounded degree expander network. However, this algorithms assumes that good nodes can send arbitrarily large-sized messages in a round.Our second algorithm is randomized and most good nodes send only small-sized messages. 1 This algorithm works in almost all d-regular graphs. It tolerates up to B(n) = n 1 2 −ξ (note that n and B(n) are unknown to the algorithm) arbitrarily (adversarially) placed Byzantine nodes, where ξ is any arbitrarily small (but fixed) positive constant. This algorithm takes O(B(n) log 2 n) rounds and outputs a (fixed) constant factor estimate of log n with probability at least 1 − o(1). The said estimate is known to most nodes, i.e.,(1 − β)n nodes for any arbitrarily small (but fixed) positive constant β.To complement our algorithms, we also present an impossibility result that shows that it is impossible to estimate the network size with any reasonable approximation with any non-trivial probability of success if the network does not have sufficient vertex expansion.Both algorithms are the first such algorithms that solve Byzantine counting in sparse, bounded degree networks under very general assumptions. Both algorithms are fully local and need no global knowledge. Our algorithms can be used for the design of efficient distributed algorithms resilient against Byzantine failures, where the knowledge of the network size -a global parameter -may not be known a priori.

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Section: Other Related Workmentioning

confidence: 99%

Section: Other Related Workmentioning

confidence: 99%

Byzantine-Resilient Counting in Networks

Chatterjee¹,

Pandurangan²,

Robinson³

2022

Preprint

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“…The value of this parameter is determined based on the number of neighbour nodes, | |, and the upper limit of faults in 's neighbourhood, . Expressly, = | | − ; | | > 2 and ≥ + 1 [37][38][39][40]. In this sense, the value depends on the network's topology and varies among nodes.…”

Section: • Receiving a Test Responsementioning

confidence: 99%

Network Coding-Based Fault Diagnosis Protocol for Dynamic Networks

2020

KSII TIIS

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Dependable functioning of dynamic networks is essential for delivering ubiquitous services. Faults are the root causes of network outages. The comparison diagnosis model, which automates fault's identification, is one of the leading approaches to attain network dependability. Most of the existing research has focused on stationary networks. Nonetheless, the time-free comparison model imposes no time constraints on the system under considerations, and it suits most of the diagnosis requirements of dynamic networks. This paper presents a novel protocol that diagnoses faulty nodes in diagnosable dynamic networks. The proposed protocol comprises two stages, a testing stage, which uses the time-free comparison model to diagnose faulty neighbour nodes, and a disseminating stage, which leverages a Random Linear Network Coding (RLNC) technique to disseminate the partial view of nodes. We analysed and evaluated the performance of the proposed protocol under various scenarios, considering two metrics: communication overhead and diagnosis time. The simulation results revealed that the proposed protocol diagnoses different types of faults in dynamic networks. Compared with most related protocols, our proposed protocol has very low communication overhead and diagnosis time. These results demonstrated that the proposed protocol is energy-efficient, scalable, and robust.

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“…Non-detectable Byzantine, are Byzantine processes whose fault cannot be detected, for example the processes that alter their internal state. In [18], Greve et al further extend that approach to propose a failure detector for detectable Byzantine in dynamic networks. In line with [25], we say that a Byzantine is detectable if it is possible for correct processes to detect it by combining information they have (e.g what they see during the execution).…”

Section: Detectable Byzantine Processesmentioning

confidence: 99%

On Fairness in Committee-based Blockchains

Amoussou-Guenou,

del Pozzo,

Potop-Butucaru

et al. 2019

Preprint

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Committee-based blockchains are among the most popular alternatives of proof-of-work based blockchains, such as Bitcoin. They provide strong consistency (no fork) under classical assumptions, and avoid using energy-consuming mechanisms to add new blocks in the blockchain. For each block, these blockchains use a committee that executes Byzantinefault tolerant distributed consensus to decide the next block they will add in the blockchain. Unlike Bitcoin, where there is only one creator per block with high probability, in committeebased blockchain any block is cooperatively created. In order to incentivize committee members to participate to the creation of new blocks rewarding schemes have to be designed. In this paper, we study the fairness of rewarding in committee-based blockchains and we provide necessary and sufficient conditions on the system communication under which it is possible to have a fair reward mechanism.

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A Time-Free Byzantine Failure Detector for Dynamic Networks

Cited by 9 publications

References 22 publications

Byzantine-Resilient Counting in Networks

Byzantine-Resilient Counting in Networks

Network Coding-Based Fault Diagnosis Protocol for Dynamic Networks

On Fairness in Committee-based Blockchains

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