A review on consensus algorithm of blockchain

Du, Mingyuan; Ma, Xiaofeng; Zhang, Zhe; Wang, Xiangwei; Chen, Qijun

doi:10.1109/smc.2017.8123011

Cited by 489 publications

(251 citation statements)

References 6 publications

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“…Paxos algorithm tries to solve the consistency problem in certain conditions for Byzantine Generals Problem. Raft achieves the same efficiency as Paxos [39], [53]. Raft and Paxos are non-Byzantine fault tolerance algorithms.…”

Section: F Raftmentioning

confidence: 99%

“…Therefore, if the leader node is maliciously infected, the entire system will be destroyed. It cannot tolerate malicious nodes and can endure 50% nodes of crash fault [53]. Since it is crucial to secure the leader node, the throughput is limited by the performance of that node.…”

Section: F Raftmentioning

confidence: 99%

“…Due to its low security and restricted throughput, it is not very appropriate for IoT networks. [37], [38], [42], [48], [52], [53], [55], [56] .…”

Section: F Raftmentioning

confidence: 99%

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A Survey on Consensus Methods in Blockchain for Resource-constrained IoT Networks

Salimitari¹,

Chatterjee²,

Fallah³

2020

Preprint

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The success of blockchain as the underlying technology for cryptocurrencies has opened up possibilities for its use in other application domains as well. The main advantages of blockchain for its potential use in other domains are its inherent security mechanisms and immunity to different attacks. A blockchain relies on a consensus method for agreeing on any new data. Most of the consensus methods which are currently used for the blockchain of different cryptocurrencies require high computational power and thus are not apt for resourceconstrained systems.In this article, we discuss and survey the various blockchain based consensus methods that are applicable to resource constrained IoT devices and networks. A typical IoT network consists of several devices which have limited computational and communications capabilities. Most often, these devices cannot perform intensive computations and are starved for bandwidth. Therefore, we discuss the possible measures that can be taken to reduce the computational power and convergence time for the underlying consensus methods. We also talk about some of the alternatives to the public blockchain like private blockchain and tangle, along with their potential adoption for IoT networks. Furthermore, we review the existing consensus methods that have been implemented and explore the possibility of utilizing them to realize a blockchain based IoT network. Some of the open research challenges are also put forward.

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Section: F Raftmentioning

confidence: 99%

Section: F Raftmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Consensus Methods in Blockchain for Resource-constrained IoT Networks

Salimitari¹,

Chatterjee²,

Fallah³

2020

Preprint

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show abstract

“…A second challenge when using ML as a PoW is that the difficulty cannot be set in advance. In most PoW blockchains, the average block interval is adjusted via an adaptive parameter, the difficulty [14]. This acts as a threshold where the first miner to exceed it wins.…”

Section: Privacy-preserving Data Miningmentioning

confidence: 99%

Privacy‐Preserving Blockchain Mining: A Proof‐of‐Useful‐Work Consensus Scheme

Turesson

Laskowski

Roatiş³

et al. 2018

SSRN Journal

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“…The main solutions proposed to address the scalability issue include (i) changes to the main protocol (consensus algorithm, parameters) and (ii) sidechains * and secondlayer solutions (see [4] for a recent technical review). Notable examples of type-(i) solutions include new consensus protocols, which would allow a faster issuance of new blocks among other new features [5]. The Lightning Network (LN), instead, is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users [6].…”

Section: Introductionmentioning

confidence: 99%

A Percolation Model for the Emergence of the Bitcoin Lightning Network

2019

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The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we explore how the distributional properties of the volume and size of transactions per user may impact its feasibility. The agents are all able to reciprocally transfer Bitcoins using the main blockchain and also -if economically convenientto open a channel on the Lightning Network and transact "off chain". We base our approach on fitness-dependent network models: as in real life, a Lightning channel is opened with a probability that depends on the "fitness" of the concurring nodes, which in turn depends on wealth and volume of transactions. The emergence of a connected component is studied numerically and analytically as a function of the parameters, and the phase transition separating regions in the phase space where the Lightning Network is sustainable or not is elucidated. We characterize the phase diagram determining the minimal volume of transactions that would make the Lightning Network sustainable for a given level of fees or, alternatively, the maximal cost the Lightning ecosystem may impose for a given average volume of transactions. The model includes parameters that could be in principle estimated from publicly available data once the evolution of the Lighting Network will have reached a stationary operable state, and is fairly robust against different choices of the distributions of parameters and fitness kernels.

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A review on consensus algorithm of blockchain

Cited by 489 publications

References 6 publications

A Survey on Consensus Methods in Blockchain for Resource-constrained IoT Networks

A Survey on Consensus Methods in Blockchain for Resource-constrained IoT Networks

Privacy‐Preserving Blockchain Mining: A Proof‐of‐Useful‐Work Consensus Scheme

A Percolation Model for the Emergence of the Bitcoin Lightning Network

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