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1
Fermon, Cécile, François-Jérôme Authier, and Laure Gallay. "Les myosites à éosinophiles idiopathiques." Les Cahiers de Myologie, no. 25 (July 2022): 6–9. http://dx.doi.org/10.1051/myolog/202225003.
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Les myosites à éosinophiles appartiennent au groupe des myopathies inflammatoires idiopathiques et sont définies par un infiltrat inflammatoire musculaire composé de polynucléaires éosinophiles. Il n’existe pas à ce jour de consensus concernant le diagnostic et le traitement de ces patients. Grâce à une revue exhaustive de la littérature, les principales caractéristiques cliniques et histologiques, ainsi que le traitement et l’évolution des patients, ont été résumés dans cette synthèse. Cette revue a permis de distinguer trois sous-groupes de myosites à éosinophiles : la forme focale, la forme diffuse et les périmyosites à éosinophiles. Un algorithme de traitement et de prise en charge est proposé, et les principaux diagnostics différentiels sont discutés.
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Waardenberg, Ashley J., and Matthew A. Field. "consensusDE: an R package for assessing consensus of multiple RNA-seq algorithms with RUV correction." PeerJ 7 (December 13, 2019): e8206. http://dx.doi.org/10.7717/peerj.8206.
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Extensive evaluation of RNA-seq methods have demonstrated that no single algorithm consistently outperforms all others. Removal of unwanted variation (RUV) has also been proposed as a method for stabilizing differential expression (DE) results. Despite this, it remains a challenge to run multiple RNA-seq algorithms to identify significant differences common to multiple algorithms, whilst also integrating and assessing the impact of RUV into all algorithms. consensusDE was developed to automate the process of identifying significant DE by combining the results from multiple algorithms with minimal user input and with the option to automatically integrate RUV. consensusDE only requires a table describing the sample groups, a directory containing BAM files or preprocessed count tables and an optional transcript database for annotation. It supports merging of technical replicates, paired analyses and outputs a compendium of plots to guide the user in subsequent analyses. Herein, we assess the ability of RUV to improve DE stability when combined with multiple algorithms and between algorithms, through application to real and simulated data. We find that, although RUV increased fold change stability between algorithms, it demonstrated improved FDR in a setting of low replication for the intersect, the effect was algorithm specific and diminished with increased replication, reinforcing increased replication for recovery of true DE genes. We finish by offering some rules and considerations for the application of RUV in a consensus-based setting. consensusDE is freely available, implemented in R and available as a Bioconductor package, under the GPL-3 license, along with a comprehensive vignette describing functionality: http://bioconductor.org/packages/consensusDE/.
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Xiong, Huanliang, Muxi Chen, Canghai Wu, Yingding Zhao, and Wenlong Yi. "Research on Progress of Blockchain Consensus Algorithm: A Review on Recent Progress of Blockchain Consensus Algorithms." Future Internet 14, no. 2 (January 30, 2022): 47. http://dx.doi.org/10.3390/fi14020047.
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Blockchain technology can solve the problem of trust in the open network in a decentralized way. It has broad application prospects and has attracted extensive attention from academia and industry. The blockchain consensus algorithm ensures that the nodes in the chain reach consensus in the complex network environment, and the node status ultimately remains the same. The consensus algorithm is one of the core technologies of blockchain and plays a pivotal role in the research of blockchain technology. This article gives the basic concepts of the blockchain, summarizes the key technologies of the blockchain, especially focuses on the research of the blockchain consensus algorithm, expounds the general principles of the consensus process, and classifies the mainstream consensus algorithms. Then, focusing on the improvement of consensus algorithm performance, it reviews the research progress of consensus algorithms in detail, analyzes and compares the characteristics, suitable scenarios, and possible shortcomings of different consensus algorithms, and based on this, studies the future development trend of consensus algorithms for reference.
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Zhong, Weiyu, Ce Yang, Wei Liang, Jiahong Cai, Lin Chen, Jing Liao, and Naixue Xiong. "Byzantine Fault-Tolerant Consensus Algorithms: A Survey." Electronics 12, no. 18 (September 8, 2023): 3801. http://dx.doi.org/10.3390/electronics12183801.
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The emergence of numerous consensus algorithms for distributed systems has resulted from the swift advancement of blockchain and its related technologies. Consensus algorithms play a key role in decentralized distributed systems, because all nodes in the system need to reach a consensus on requests or commands through consensus algorithms. In a distributed system where nodes work together to reach consensus, there may be Byzantine nodes present. The emergence of Byzantine nodes will affect the consensus of nodes in the distributed system. Therefore, tolerating Byzantine nodes in a distributed system and then reaching a consensus is an essential function of a consensus algorithm. So far, many Byzantine fault-tolerant (BFT) consensus algorithms have emerged, and there are correspondingly many methods to improve the performance of these algorithms. In order to allow researchers to have a clearer understanding of the existing methods, this paper systematically investigated and studied the research progress of the current Byzantine fault-tolerant consensus algorithm. The scope of the research ranged from the classic Byzantine consensus algorithm to some of the latest Byzantine consensus algorithms. The articles were classified according to the methods used to improve the Byzantine consensus algorithm. Through classification and centralized analysis and discussion, we achieved a clearer understanding of the development of Byzantine consensus algorithms and, at the same time, clarified the advantages and disadvantages of this type of method and the latest research progress using this method. At the end of this article, an in-depth discussion and analysis is also presented. By analyzing the impact of the use of these methods on the performance of the BFT consensus algorithm, it is proposed that future research can be improved.
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Ge, Lina, Jie Wang, and Guifen Zhang. "Survey of Consensus Algorithms for Proof of Stake in Blockchain." Security and Communication Networks 2022 (May 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/2812526.
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As the core of blockchain technology, the consensus algorithm directly affects the security, stability, and decentralisation of the blockchain and numerous other important characteristics. Choosing an appropriate consensus algorithm for different scenarios is currently a challenge in the implementation of blockchain applications. This paper classifies the improvement schemes of proof of stake (PoS) into three categories: PoS-based consensus algorithms, PoS- and PoW-based consensus algorithms, and PoS- and BFT-based consensus algorithms. First, the study introduces the PoS and PoS consensus algorithm variants and then summarises the core ideas, effects, advantages, and disadvantages of these algorithms. Subsequently, the performances of the improved algorithms are compared. Finally, the main improved methods are summarised, and the most common network security attacks are discussed. The study lays a foundation for the main improvement directions of PoS in the future, hoping to provide a reference for researchers to help them select and design consensus algorithms in different application scenarios while also helping the evolution of consensus algorithms and the implementation of blockchain applications.
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Palomares, A., M. Rebollo, and C. Carrascosa. "Supportive consensus." PLOS ONE 15, no. 12 (December 17, 2020): e0243215. http://dx.doi.org/10.1371/journal.pone.0243215.
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The paper is concerned with the consensus problem in a multi-agent system such that each agent has boundary constraints. Classical Olfati-Saber’s consensus algorithm converges to the same value of the consensus variable, and all the agents reach the same value. These algorithms find an equality solution. However, what happens when this equality solution is out of the range of some of the agents? In this case, this solution is not adequate for the proposed problem. In this paper, we propose a new kind of algorithms called supportive consensus where some agents of the network can compensate for the lack of capacity of other agents to reach the average value, and so obtain an acceptable solution for the proposed problem. Supportive consensus finds an equity solution. In the rest of the paper, we define the supportive consensus, analyze and demonstrate the network’s capacity to compensate out of boundaries agents, propose different supportive consensus algorithms, and finally, provide some simulations to show the performance of the proposed algorithms.
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Acharya, Deep Shekhar, and Sudhansu Kumar Mishra. "Optimal Consensus Recovery of Multi-agent System Subjected to Agent Failure." International Journal on Artificial Intelligence Tools 29, no. 06 (September 2020): 2050017. http://dx.doi.org/10.1142/s0218213020500177.
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Multi-Agent Systems are susceptible to external disturbances, sensor failures or collapse of communication channel/media. Such failures disconnect the agent network and thereby hamper the consensus of the system. Quick recovery of consensus is vital to continue the normal operation of an agent-based system. However, only limited works in the past have investigated the problem of recovering the consensus of an agent-based system in the event of a failure. This work proposes a novel algorithmic approach to recover the lost consensus, when an agent-based system is subject to the failure of an agent. The main focus of the algorithm is to reconnect the multi-agent network in a way so as to increase the connectivity of the network, post recovery. The proposed algorithm may be applied to both linear and non-linear continuous-time consensus protocols. To verify the efficiency of the proposed algorithm, it has been applied and tested on two multi-agent networks. The results, thus obtained, have been compared with other state-of-the-art recovery algorithms. Finally, it has been established that the proposed algorithm achieves better connectivity and therefore, faster consensus when compared to the other state-of-the-art.
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Bakhvalova, Ekaterina Alexandrovna, and Vladimir Anatolievich Sudakov. "Research of consensus algorithms for blockchain platforms." Keldysh Institute Preprints, no. 26 (2021): 1–16. http://dx.doi.org/10.20948/prepr-2021-26.
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In this paper, several consensus algorithms are investigated, a comparative analysis of these algorithms is made, the results of which are important in the context of the active growth of the cryptocurrency market. In addition, in the context of pandemics, the creation of blockchain technologies for the distributed storage of reliable medical data is relevant. The key properties of consensus algorithms are highlighted, and a detailed analysis of the algorithm of the promising Istanbul BFT algorithm is carried out. Using multi-criterion analysis of alternatives, it is shown how you can select the appropriate consensus algorithm for the needs of specific tasks.
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Hanna, Fouad, Lionel Droz-Bartholet, and Jean-Christophe Lapayre. "Toward a Faster Fault Tolerant Consensus to Maintain Data Consistency in Collaborative Environments." International Journal of Cooperative Information Systems 26, no. 03 (August 14, 2017): 1750002. http://dx.doi.org/10.1142/s0218843017500022.
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The consensus problem has become a key issue in the field of collaborative telemedicine systems because of the need to guarantee the consistency of shared data. In this paper, we focus on the performance of consensus algorithms. First, we studied, in the literature, the most well-known algorithms in the domain. Experiments on these algorithms allowed us to propose a new algorithm that enhances the performance of consensus in different situations. During 2014, we presented our very first initial thoughts to enhance the performance of the consensus algorithms, but the proposed solution gave very moderate results. The goal of this paper is to present a new enhanced consensus algorithm, named Fouad, Lionel and J.-Christophe (FLC). This new algorithm was built on the architecture of the Mostefaoui-Raynal (MR) consensus algorithm and integrates new features and some known techniques in order to enhance the performance of consensus in situations where process crashes are present in the system. The results from our experiments running on the simulation platform Neko show that the FLC algorithm gives the best performance when using a multicast network model on different scenarios: in the first scenario, where there are no process crashes nor wrong suspicion, and even in the second one, where multiple simultaneous process crashes take place in the system.
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Khan, Dr Kashif Mehboob, Muhammad Abdullah Hayat, and Rana Muhammad Ibrahim. "Investigating the Impact of Consensus Algorithm on Scalability in Blockchain Systems." Sir Syed University Research Journal of Engineering & Technology 12, no. 2 (December 25, 2022): 01–06. http://dx.doi.org/10.33317/ssurj.427.
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In the current era, blockchain has emerged as one the best and promising technology. All the cryptocurrencies have also gained a lot of popularity around the globe which are based on blockchain technology. Blockchain provides a distributed architecture, in which transactions are verified by different validators using different algorithms and then are stored in distributed ledger. The verification of transactions is done using consensus algorithms which verifies that incoming transaction is correct and reliable by different distributed nodes working in a peer-to-peer network. Consensus algorithms ensure the integrity and security of blockchain. There are various types of consensus algorithms used in blockchain technology which are used depending on the architecture and usage, some of the consensus algorithms are Proof of Work (PoW), Proof of Stake (PoS) etc. The Proof of Work algorithm is most widely used across the globe by the community. It is used by many popular cryptocurrency networks like Litecoin and Bitcoin. It requires larger computation power while verifying transactions. The selection of a consensus algorithm is one the most important parts of blockchain, as the consensus mechanism is considered to be the core of a network. It is easier to predict and guarantee the security, reliability, fault tolerance, and recoverability of the system if the correct consensus protocol is selected. A single algorithm can never fulfill all the requirements, there is always a tradeoff in the selection of consensus algorithms. Therefore, it is very important to select the best suited consensus algorithm for the network as the consensus mechanism validates transactions without any third-party platform and prevents malicious activities in the network. This paper investigates the comparison among types of consensus algorithms and their effectiveness and viability.
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Capocasale, Vittorio. "Trapdoor proof of work." PeerJ Computer Science 10 (January 19, 2024): e1815. http://dx.doi.org/10.7717/peerj-cs.1815.
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Consensus algorithms play a crucial role in facilitating decision-making among a group of entities. In certain scenarios, some entities may attempt to hinder the consensus process, necessitating the use of Byzantine fault-tolerant consensus algorithms. Conversely, in scenarios where entities trust each other, more efficient crash fault-tolerant consensus algorithms can be employed. This study proposes an efficient consensus algorithm for an intermediate scenario that is both frequent and underexplored, involving a combination of non-trusting entities and a trusted entity. In particular, this study introduces a novel mining algorithm, based on chameleon hash functions, for the Nakamoto consensus. The resulting algorithm enables the trusted entity to generate tens of thousands blocks per second even on devices with low energy consumption, like personal laptops. This algorithm holds promise for use in centralized systems that require temporary decentralization, such as the creation of central bank digital currencies where service availability is of utmost importance.
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Mohammed, Mohanad A., and Hala B. Abdul Wahab. "Proposed New Blockchain Consensus Algorithm." International Journal of Interactive Mobile Technologies (iJIM) 16, no. 20 (October 31, 2022): 162–76. http://dx.doi.org/10.3991/ijim.v16i20.35549.
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Blockchain technology considers the central technology that is used within many applications used frequently with human life. And the primary core of the blockchain is the consensus algorithm which may affect the security of the chain as well as the required resource consumption which affect mainly the blockchain performance directly. In recent years many consensus algorithms have been used and proposed such as proof of work (PoW) and proof of stake (PoS) and many others. However, these algorithms still need some improvement to the security and system resource consumption which will reduce the need for a huge amount of energy and save the environment as well as let the blockchain be useable within low computation ability devices such as the internet of things devices (IoT). This paper proposes a new consensus algorithm that ensures the integrity and authorization of nodes participating in the validation of the transaction and only a predefined number of nodes chosen randomly to participate in block addition which reduces the need for high computations power for mining and voting. The proposed algorithm needs lower time and computation costs comparable to the standard POW algorithm.
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Öksüz, Halil Yiğit, and Mehmet Akar. "Distributed resilient consensus: a non-parametric approach." Transactions of the Institute of Measurement and Control 41, no. 8 (August 9, 2018): 2124–34. http://dx.doi.org/10.1177/0142331218785673.
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In this paper, two parameter-independent fault-tolerant consensus algorithms are proposed to address the consensus problem in the presence of misbehaving agents. The first algorithm relies on adaptively estimating the number of faulty agents in the network by using a distributed fault-detection scheme. It is shown that this algorithm converges if the network of non-faulty agents is ( f+1)-robust, where f is the number of faulty agents in the network. The second algorithm is a non-parametric Mean-Subsequence-Reduced algorithm whose convergence is guaranteed if the network of non-faulty nodes is ( f+1)-robust and all non-faulty nodes have the same number of in-neighbours. Neither algorithm requires initial knowledge on the number of faulty agents in the network. The efficacy of the algorithms are illustrated with simulation results.
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Safaryan, Olga A., Kirill S. Lemeshko, Alexey N. Beskopylny, Larissa V. Cherckesova, and Denis A. Korochentsev. "Mathematical Analysis of Parametric Characteristics of the Consensus Algorithms Operation with the Choice of the Most Priority One for Implementation in the Financial Sphere." Electronics 10, no. 21 (October 30, 2021): 2659. http://dx.doi.org/10.3390/electronics10212659.
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Blockchain is one of the leading data transfer technologies that eliminate the need for centralized management through consensus algorithms. This article describes the consensus algorithms, their benefits, and their applications within a micropayment system in the financial sector. Preliminary studies have shown that the performance of distributed databases largely depends on the chosen consensus algorithm. The main task of the study is to create a mathematical model to assess their performance. The most popular crypto projects and the consensus algorithms are analyzed to determine their performance. The obtained model was tested by calculating the parameters of the distributed register based on the directed acyclic graph algorithm and calculating the parameters of other algorithms used. The result is a mathematical model for evaluating the parametric characteristics of the work of consensus algorithms with the choice of the most priority one for implementation in the financial sector. The analysis focuses on the mathematical steps taken by each consensus algorithm. The data obtained using the developed mathematical model demonstrates that PoW, PoS, and DAG algorithms depend on various resources, such as computing power, the number of connected nodes, and the speed of receiving transactions.
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Yang, Janghoon, and Yungho Choi. "LQR-Based Sparsification Algorithms of Consensus Networks." Electronics 10, no. 9 (May 3, 2021): 1082. http://dx.doi.org/10.3390/electronics10091082.
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The performance of multiagent systems depends heavily on information flow. As agents are populated more densely, some information flow can be redundant. Thus, there can be a tradeoff between communication overhead and control performance. To address this issue, the optimization of the communication topology for the consensus network has been studied. In this study, three different suboptimal topology algorithms are proposed to minimize the linear quadratic regulator (LQR) cost considering the communication penalty, since the optimal solution requires a brute-force search, which has exponential complexity. The first two algorithms were designed to minimize the maximum eigenvalue of the Riccati matrix for the LQR, while the third algorithm was designed to remove edges sequentially in a greedy manner through evaluating the LQR cost directly. The first and second algorithms differ in that the active edges of a consensus network are determined at the end of the iterations in the first, while sequentially in the second. Numerical evaluations show that the proposed algorithms reduce the LQR cost significantly by optimizing communication topology, while the proposed algorithm may achieve optimal performance with a properly chosen parameterization for a small consensus network. While the three algorithms show similar performance with the increasing number of agents, the quantized terminal cost matrix optimization (QTCMO) algorithm shows significantly less complexity within the order of several tenths than those of the other two algorithms.
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Liu, Li Min, Xiao Ping Fan, and Yue Shan Xie. "Consensus Function Based on Matrix Factorization." Applied Mechanics and Materials 235 (November 2012): 15–19. http://dx.doi.org/10.4028/www.scientific.net/amm.235.15.
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Clustering ensemble has been known as an effective method to improve the robustness and stability of clustering analysis. Clustering ensemble solves the problem in two steps:firstly,generating a large set of clustering partitions based on the clustering algorithms;secondly,combining them using a consensus function to get the final clustering result. The key technology of clustering ensemble is the proper consensus function. Recent research proposed using the matrix factorization to solve clustering ensemble. In this paper, we firstly analyze some traditional matrix factorization algorithms; secondly, we propose a new consensus function using binary nonnegative matrix factorization (BMF) and give the optimization algorithm of BMF; lastly, we propose the new framework of clustering ensemble algorithm and give some experiments on UCI Machine Learning Repository. The experiments show that the new algorithm is effective and clustering performance could be significantly improved.
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Kim, Heesang, and Dohoon Kim. "A Taxonomic Hierarchy of Blockchain Consensus Algorithms: An Evolutionary Phylogeny Approach." Sensors 23, no. 5 (March 2, 2023): 2739. http://dx.doi.org/10.3390/s23052739.
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Countless endeavors have been undertaken to address the Byzantine Generals Problem, a generalization of the Two Generals Problem. The emergence of proof of work (PoW) for Bitcoin has led to various consensus algorithms diverging, and comparable existing consensus algorithms are being gradually utilized interchangeably, or only developed for each specific application domain. Our approach employs an evolutionary phylogeny method to classify blockchain consensus algorithms based on their historical development and current usage. To demonstrate the relatedness and lineage of distinct algorithms, as well as to support the recapitulation theory, which posits that the evolutionary history of its mainnets is mirrored in the development of an individual consensus algorithm, we present a taxonomy. We have created a comprehensive classification of past and present consensus algorithms that serves to organize this swift consensus algorithm evolution period. By recognizing similarities, we have compiled a list of different verified consensus algorithms and performed clustering on over 38 of these. Our new taxonomic tree presents five taxonomic ranks, including the evolutionary process and decision-making method, as a technique for analyzing correlation. Through the examination of the evolution and utilization of these algorithms, we have developed a systematic and hierarchical taxonomy that enables the grouping of consensus algorithms into distinct categories. The proposed method classifies various consensus algorithms according to taxonomic ranks and aims to reveal the direction of research on the application of blockchain consensus algorithms for each domain.
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Seo, Jungwon, Deokyoon Ko, Suntae Kim, and Sooyong Park. "A Coordination Technique for Improving Scalability of Byzantine Fault-Tolerant Consensus." Applied Sciences 10, no. 21 (October 28, 2020): 7609. http://dx.doi.org/10.3390/app10217609.
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Among various consensus algorithms, the Byzantine Fault Tolerance (BFT)-based consensus algorithms are broadly used for private blockchain. However, as BFT-based consensus algorithms are structured for all participants to take part in a consensus process, a scalability issue becomes more noticeable. In this approach, we introduce a consensus coordinator to execute a conditionally BFT-based consensus algorithm by classifying transactions. Transactions are divided into equal and unequal transactions. Moreover, unequal transactions are divided again and classified as common and trouble transactions. After that, a consensus algorithm is only executed for trouble transactions, and BFT-based consensus algorithms can achieve scalability. For evaluating our approach, we carried out three experiments in response to three research questions. By applying our approach to PBFT, we obtained 4.75 times better performance than using only PBFT. In the other experiment, we applied our approach to IBFT of Hyperledger Besu, and our result shows a 61.81% performance improvement. In all experiments depending on the change of the number of blockchain nodes, we obtained the better performance than original BFT-based consensus algorithms; thus, we can conclude that our approach improved the scalability of original BFT-based consensus algorithms. We also showed a correlation between performance and trouble transactions associated with transaction issue intervals and the number of blockchain nodes.
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Wang, Wen Kai, and Huan Xin Peng. "Pseudo Multi-Hop Distributed Consensus with Adaptive Quantization." Advanced Materials Research 591-593 (November 2012): 1432–35. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.1432.
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The convergence accuracy of distributed consensus with quantization communication depends on the quantization error and the convergence rate of the distributed consensus algorithm. In order to improve the accuracy and the convergence rate of distributed consensus under quantized communication, in the paper, based on the adaptively quantized scheme, we propose the pseudo multi-hop adaptively quantized distributed consensus algorithm. We analyze the convergence performance of the pseudo multi-hop adaptively quantized distributed consensus algorithm, and the algorithm can achieves a consensus in a mean square sense. Simultaneously, Simulations are present. Results show that the pseudo multi-hop adaptively quantized distributed consensus algorithm can reach an average consensus, and its convergence rate is higher than those of the other adaptive quantized distributed consensus algorithms.
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Mingjie Zhao, Mingjie Zhao, Cheng Dai Mingjie Zhao, and Bing Guo Cheng Dai. "Safe and Efficient Delegated Proof of Stake Consensus Mechanism Based on Dynamic Credit in Electronic Transaction." 網際網路技術學刊 24, no. 1 (January 2023): 123–33. http://dx.doi.org/10.53106/160792642023012401012.
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<p>The sector of electronic transactions based on blockchain technology is expanding quickly thanks to the reliability of the consensus mechanism, which offers a new technical path for developing the financial industry. The consensus algorithms cannot support the safety and efficiency required for electronic transaction scenarios as they are right now. We propose an enhanced DPoS algorithm based on dynamic credit (DC-DPoS) to address the aforementioned issue. It has a system for node classification, dynamic credit evaluation, and a consistency algorithm that combines voting and random selection. According to theoretical research and simulated experiments, our algorithm improves security while achieving reduced latency and greater throughput. It presents a fresh thought for enhancing the functionality of the blockchain system while also satisfying the fundamental technical criteria of electronic transactions.</p> <p> </p>
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Katti, Amogh, Giuseppe Di Fatta, Thomas Naughton, and Christian Engelmann. "Epidemic failure detection and consensus for extreme parallelism." International Journal of High Performance Computing Applications 32, no. 5 (February 1, 2017): 729–43. http://dx.doi.org/10.1177/1094342017690910.
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Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum’s User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. Stochastic pinging is used to quickly detect failures during the execution of the algorithm, failures are then disseminated to all the fault-free processes in the system and consensus on the failures is detected using the three consensus techniques. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that the stochastic pinging detects all the failures in the system. In all the algorithms, the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.
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Kenyeres, Martin, and Jozef Kenyeres. "Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study." Future Internet 15, no. 5 (May 16, 2023): 183. http://dx.doi.org/10.3390/fi15050183.
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Consensus-based data aggregation in d-regular bipartite graphs poses a challenging task for the scientific community since some of these algorithms diverge in this critical graph topology. Nevertheless, one can see a lack of scientific studies dealing with this topic in the literature. Motivated by our recent research concerned with this issue, we provide a comparative study of frequently applied consensus algorithms for distributed averaging in d-regular bipartite graphs in this paper. More specifically, we examine the performance of these algorithms with bounded execution in this topology in order to identify which algorithm can achieve the consensus despite no reconfiguration and find the best-performing algorithm in these graphs. In the experimental part, we apply the number of iterations required for consensus to evaluate the performance of the algorithms in randomly generated regular bipartite graphs with various connectivities and for three configurations of the applied stopping criterion, allowing us to identify the optimal distributed consensus algorithm for this graph topology. Moreover, the obtained experimental results presented in this paper are compared to other scientific manuscripts where the analyzed algorithms are examined in non-regular non-bipartite topologies.
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Wu, Yaqin, Pengxin Song, and Fuxin Wang. "Hybrid Consensus Algorithm Optimization: A Mathematical Method Based on POS and PBFT and Its Application in Blockchain." Mathematical Problems in Engineering 2020 (April 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/7270624.
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Blockchain is a new technology for processing complex and disordered information with respect to business and other industrial applications. This work is aimed at studying the consensus algorithm of blockchain to improve the performance of blockchain. Despite their advantages, the proof of stake (POS) algorithm and the practical Byzantine fault tolerance (PBFT) algorithm have high latency, low throughput, and poor scalability. In this paper, a blockchain hybrid consensus algorithm which combines advantages of the POS and PBFT algorithms is proposed, and the algorithm is divided into two stages: sortition and witness. The proposed algorithm reduces the number of consensus nodes to a constant value by verifiable pseudorandom sortition and performs transaction witness between nodes. The algorithm is improved and optimized from three dimensions: throughput, latency, and scalability. The experimental results show that the improved hybrid consensus algorithm is significantly superior to the previous single algorithms for its excellent scalability, high throughput, and low latency.
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Zhuravel, S., O. Shpur, and Yu Pyrih. "METHOD OF ACHIEVING CONSENSUS IN DISTRIBUTED SERVICE." Information and communication technologies, electronic engineering 2, no. 2 (December 2022): 58–66. http://dx.doi.org/10.23939/ictee2022.02.058.
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This article examines the problems of distributed algorithms and proposes their solution using temporal analysis. There are many things that can go wrong in distributed systems that can cause the system to crash. The solution to this is to build a system that can withstand the problems that arise during its operation. It turns out that having an algorithm capable of reaching consensus is extremely important for systems that want to function properly despite network failures. Although consensus is omitted in performance-oriented systems, they still rely heavily on systems that implement consensus algorithms for them (such as Zookeeper, etc.) to handle the consensus-reduced task, while at the same time having some weaker consistency model. In turn, the algorithms available today have several problems, the solution of which will significantly increase the performance of the algorithms and, as a result, the systems that use them. This article discusses the problems that arise in existing implementations and presents a data analysis technique and model for solving one of the algorithm problem.
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Yang, Feng, Weikang Tang, and Yan Liang. "A novel track initialization algorithm based on random sample consensus in dense clutter." International Journal of Advanced Robotic Systems 15, no. 6 (November 1, 2018): 172988141881263. http://dx.doi.org/10.1177/1729881418812632.
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Track initialization in dense clutter environments is an important topic and still a challenging task. Most traditional track initialization techniques firstly consider all possible associated measurement combinations and select the optimal one as an initialized track. Therefore, dense clutter brings great challenges to traditional algorithms. Random sample consensus algorithm, which is different from traditional algorithms, starts from minimum measurements. It samples randomly minimum measurements to establish hypotheses and verifies them through remaining measurements. However, the randomness of sampling influences algorithm performance, especially in dense clutter. A novel track initialization based on random sample consensus, named density-based random sample consensus algorithm, is proposed. It utilizes the fact that sequential measurements originating from the same target are contiguous while clutter is separated in space–time domain. The algorithm defines the density property of measurements to decrease the randomness in sampling procedure and increase the efficiency of track initialization. The experimental results show that the density-based random sample consensus is more superior to random sample consensus, the Hough transform algorithm, and logic-based algorithm.
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Hattab, Siham, and Imad Fakhri Taha Alyaseen. "Consensus Algorithms Blockchain: A comparative study." International Journal on Perceptive and Cognitive Computing 5, no. 2 (December 15, 2019): 66–71. http://dx.doi.org/10.31436/ijpcc.v5i2.103.
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A blockchain is a Distributed Ledger Technology that has been defined as a “distributed, shared, encrypted database that serves as an irreversible and incorruptible repository of information. Blockchain can be defined as a peer-to-peer distributed ledger that is cryptographically secure, append-only, immutable and updatable only via consensus or agreement among peers. In blockchain platforms, each transaction in the public ledger is verified by consensus of the majority of the system participants in a transparent and secure way. The consensus algorithm refers to the process of attaining an unified agreement on the state of the network in a decentralized way and to facilitate the verification and validation of information being added to the blockchain. This paper aims at providing a comparison between most of the recent consensus algorithms regarding the scalability of the algorithm; the type of blockchain, node identity, the performance of the algorithm (in terms of throughput & latency) and Adversial Tolerance and to deliver a solid basis for discussions about current statistics. In this research, we also presented a new category of the Blockchain consensus algorithms, which consist of three groups as follows; the proof based on Hardware, the proof based on stake, and the proof based on voting.
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Wang, Baocheng, Zetao Li, and Haibin Li. "Hybrid Consensus Algorithm Based on Modified Proof-of-Probability and DPoS." Future Internet 12, no. 8 (July 24, 2020): 122. http://dx.doi.org/10.3390/fi12080122.
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As the core of blockchain technology, the consensus algorithm plays an important role in determining the security, data consistency, and efficiency of blockchain systems. The existing mainstream consensus algorithm is experiencing difficulties satisfying the needs of efficiency, security, and decentralization in real-world scenarios. This paper proposes a hybrid consensus algorithm based on modified Proof-of-Probability and Delegated Proof-of-Stake. In this method, the work of block generation and validation is, respectively, completed by the nodes using the modified Proof-of-Probability consensus algorithm and Delegated Proof-of-Stake consensus algorithm. When a transaction occurs, the system sends several target hash values to the whole network. Each modified Proof-of-Probability node has a different sorting algorithm, so they have different mining priorities. Every time a hash is decrypted by a modified Proof-of-Probability node, the modulo operation is done to the value of nonce, which is then compared with the expected value given by the supernode selected by the Delegated Proof-of-Stake nodes. If they are not the same, the Proof-of-Probability node enters the waiting time and the other Proof-of-Probability nodes continue to mine. By adopting two consensus algorithms, the malicious nodes must control more than 51% of the nodes that adopt the two consensus algorithms, at the same time, to effectively attack the system, that is, they must have more than 51% of the computing power and more than 51% of the tokens. This not only increases the cost of malicious attacks, but also reduces waste of computing power. In addition, the efficiency of the DPoS algorithm makes up for the deficiency of the PoP algorithm in system efficiency, and the mining behavior based on probability in the PoP algorithm also significantly weakens the ability of supernodes in the DPoS algorithm to conduct monopoly behavior or other malicious behaviors. In a word, the combination of the two algorithms makes the system perform better in terms of security, system efficiency, and decentralization.
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Peng, Huan Xin, Bin Liu, and Wen Kai Wang. "Pseudo Two-Hop Distributed Consensus with Noise." Applied Mechanics and Materials 511-512 (February 2014): 393–96. http://dx.doi.org/10.4028/www.scientific.net/amm.511-512.393.
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In this paper, we analyze the pseudo two-hop distributed consensus algorithm with communication noise. If there is communication noise among agents, the convergence performance of distributed consensus algorithms degrades. Supposing that the communication noises are zero-mean Gaussian white noise, and the noises are irrelevant and independent in time and spatial, we analyze the convergence performance of the pseudo two-hop distributed consensus algorithm with noise, and calculate mean square errors and the upper bound of mean-square error of the pseudo two-hop distributed consensus algorithm. Finally, simulation results are provided to verify these analytical results.
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Wei, Runze. "The advance of consensus algorithm in blockchain." Applied and Computational Engineering 18, no. 1 (October 23, 2023): 5–15. http://dx.doi.org/10.54254/2755-2721/18/20230954.
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As a distributed ledger technology, blockchain has found widespread use in a variety of industries, including finance, the Internet of Things (IoT), healthcare, and manufacturing. This technology addresses the trust issue by converting a low-trust centralized ledger into a highly trusted distributed ledger maintained by various entities. Consensus algorithms are one of the fundamental building blocks of the blockchain, controlling how nodes cooperate and synchronize data to perform secure and reliable activities in a decentralized setting. This paper examines the extant mainstream consensus algorithms, introduces six representative consensus algorithms, analyses their benefits and drawbacks, and discusses the application scenarios and suitability of each consensus algorithm in various blockchain platforms.
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Gupta, Nishant, and Ankit Kumar Jain. "RSA Based Consensus Algorithm for Lightweight Private Blockchain Network." ITM Web of Conferences 54 (2023): 03003. http://dx.doi.org/10.1051/itmconf/20235403003.
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Consensus algorithms are essential for achieving agreement among nodes in blockchain systems. However, traditional consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) can be resource-intensive and unsuitable for lightweight private blockchain applications. This paper proposes using the RSA (Rivest–Shamir–Adleman) encryption algorithm as a consensus algorithm for a lightweight private blockchain in the context of a college placement system. RSA offers several advantages over traditional consensus algorithms, including simplicity, efficiency, and security. Moreover, RSA can be implemented on resource-constrained nodes, making it a promising solution for lightweight blockchain applications. The resource constrained nodes are students, academic department, training and placement cell department, and placement cell coordinator. The company acts as a client. The movement of the student’s data to companies is recorded as transactions on the distributed ledger or blockchain, allowing the student to track its progress.
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Liu, Peng, Shuang Ren, Jun Wang, Shanshan Yuan, Yiying Nian, and Yifan Li. "A Blockchain Consensus Optimization-Based Algorithm for Food Traceability." Mobile Information Systems 2022 (March 31, 2022): 1–7. http://dx.doi.org/10.1155/2022/1529983.
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At present, blockchain technology is more and more widely used in the field of food traceability, and good results have been achieved. However, many of the current blockchain technologies and algorithms are not developed for the specific situation of food traceability, resulting in resource waste and low computational efficiency. In view of these problems, this paper analyzes and summarizes the classic distributed consensus mechanism in blockchain technology, focusing on the PBFT (practical Byzantine fault tolerance) consensus mechanism and the existing problems related to the improvement scheme. In order to solve the problem of low efficiency of a consensus algorithm in a food traceability scenario, this paper proposes a blockchain consensus algorithm suitable for the food traceability scenario based on clustering and food credit. In addition, the differences between the improved algorithm and the classical Byzantine consensus algorithm in consensus algorithm time and communication times are analyzed through experiments and simulations. The consensus efficiency of the improved algorithm in this paper is significantly improved, which can greatly reduce the application difficulty of blockchain in food traceability.
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Zheng, Qingxiao, Lingfeng Wang, Jin He, and Taiyong Li. "KNN-Based Consensus Algorithm for Better Service Level Agreement in Blockchain as a Service (BaaS) Systems." Electronics 12, no. 6 (March 16, 2023): 1429. http://dx.doi.org/10.3390/electronics12061429.
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With services in cloud manufacturing expanding, cloud manufacturers increasingly use service level agreements (SLAs) to guarantee business processing cooperation between CSPs and CSCs (cloud service providers and cloud service consumers). Although blockchain and smart contract technologies are critical innovations in cloud computing, consensus algorithms in Blockchain as a Service (BaaS) systems often overlook the importance of SLAs. In fact, SLAs play a crucial role in establishing clear commitments between a service provider and a customer. There are currently no effective consensus algorithms that can monitor the SLA and provide service level priority. To address this issue, we propose a novel KNN-based consensus algorithm that classifies transactions based on their priority. Any factor that impacts the priority of the transaction can be used to calculate the distance in the KNN algorithm, including the SLA definition, the smart contract type, the CSC type, and the account type. This paper demonstrates the full functionality of the enhanced consensus algorithm. With this new method, the CSP in BaaS systems can provide improved services to the CSC. Experimental results obtained by adopting the enhanced consensus algorithm show that the SLA is better satisfied in the BaaS systems.
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Peng, Huan Xin, Bin Liu, and De Hong Xu. "Pseudo Two-Hop Distributed Consensus Algorithm with Time-Delay." Applied Mechanics and Materials 364 (August 2013): 192–96. http://dx.doi.org/10.4028/www.scientific.net/amm.364.192.
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In this paper, we analyze the pseudo two-hop distributed consensus algorithm with time-delay. If there is time-delay among agents, the convergence performance of distributed consensus algorithms degrades. Supposing that the time-delay in every link is identical and invariant in time and spatial, we analyze the convergence performance of the pseudo two-hop distributed consensus algorithm with time-delay, and calculate the maximum time-delay that the pseudo two-hop algorithm remains stable. Finally, simulation results are provided to verify these analytical results.
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Abdulghafor, Rawad, Sherzod Turaev, Akram Zeki, and Adamu Abubaker. "Nonlinear Convergence Algorithm: Structural Properties with Doubly Stochastic Quadratic Operators for Multi-Agent Systems." Journal of Artificial Intelligence and Soft Computing Research 8, no. 1 (January 1, 2018): 49–61. http://dx.doi.org/10.1515/jaiscr-2018-0003.
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Abstract This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The first part undertakes systematic review of consensus problems. Convergence was generated via extreme doubly stochastic quadratic operators (EDSQOs) in the other part. However, this work was able to formulate convergence algorithms from doubly stochastic matrices, majorization theory, graph theory and stochastic analysis. We develop two algorithms: 1) the nonlinear algorithm of extreme doubly stochastic quadratic operator (NLAEDSQO) to generate all the convergent EDSQOs and 2) the nonlinear convergence algorithm (NLCA) of EDSQOs to investigate the optimal consensus for MAS. Experimental evaluation on convergent of EDSQOs yielded an optimal consensus for MAS. Comparative analysis with the convergence of EDSQOs and DeGroot model were carried out. The comparison was based on the complexity of operators, number of iterations to converge and the time required for convergences. This research proposed algorithm on convergence which is faster than the DeGroot linear model.
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Lei, Bin, and Liang Cai Zeng. "Consensus Algorithm for Swarm Robotics Cooperative Control." Advanced Materials Research 201-203 (February 2011): 1854–57. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.1854.
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A critical problem for swarm robotics cooperative control is to determine appropriate consensus algorithms so that a group of robots can reach consensus on the values of coordination data. In this paper, we defined the Information Interactive Graph ( IIG ) and the Information Interactive Matrix ( IIM ) to represent the information interaction relationship between each robot based on algebra graph theroy. Proofed the necessary and/or sufficient conditions for consensus and presented some consensus algorithms under static topology. Finally, simulation results showed that our algorithm can make a swarm of robots reach a consensus on the shared coordination data.
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Mohanan, Nishitha, and Sudha D. "Comparative Study of Blockchain Consensus Algorithms in Cryptocurrency." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 09 (September 1, 2023): 1–11. http://dx.doi.org/10.55041/ijsrem25787.
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Blockchain technology serves as a cornerstone for various cryptocurrencies, with current research primarily focusing on its security aspects due to its inherent qualities such as stability, immutability, security, and decentralization. Similar to other distributed systems, Blockchain relies on consensus algorithms to achieve agreement and safeguard its network. In recent years, diverse consensus algorithms have emerged within the Blockchain ecosystem, playing a pivotal role in upholding the security and integrity of distributed networks in blockchain technology. These algorithms are fundamental in maintaining trust within the blockchain technology realm. They can be categorized into two types: proof-based and voting-based. This paper presents some of the prominent consensus algorithms from these two categories while scrutinizing their respective strengths, weaknesses, and the specific types of blockchains to which these algorithms are applicable. Keywords—Blockchain, consensus algorithm, PoS, Pow, DPoS, PBFT
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Stanković, Maja, and Dragan Antić. "DISTRIBUTED CONSENSUS-BASED CALIBRATION OF NETWORKED CONTROL SYSTEMS." Facta Universitatis, Series: Automatic Control and Robotics 18, no. 2 (January 27, 2020): 095. http://dx.doi.org/10.22190/fuacr1902095s.
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In this paper a new algorithm for distributed blind macro-calibration of Networked Control Systems is presented. It is assumed that the measured signal is stochastic and unknown. The algorithm is in the form of recursions of gradient type for estimation of the correction parameters for sensor gains and offsets. The recursion for gain correction is autonomous, derived from the measurement increments. The recursion for offset correction is based on differences between local measurements and utilizes the results of gain correction. It is proved that the algorithm provides asymptotic convergence to consensus in the sense that the corrected gains and offsets are equal for all sensors. It is demonstrated that the adopted structure of the algorithm enables obtaining high convergence rate, superior to the algorithms existing in the literature. Simulation results are provided illustrating the proposed algorithm properties.
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Nikkhah, Vageehe, Seyed M. Babamir, and Seyed S. Arab. "Estimating Bifurcating Consensus Phylogenetic Trees Using Evolutionary Imperialist Competitive Algorithm." Current Bioinformatics 14, no. 8 (December 13, 2019): 728–39. http://dx.doi.org/10.2174/1574893614666190225145620.
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Background:One of the important goals of phylogenetic studies is the estimation of species-level phylogeny. A phylogenetic tree is an evolutionary classification of different species of creatures. There are several methods to generate such trees, where each method may produce a number of different trees for the species. By choosing the same proteins of all species, it is possible that the topology and arrangement of trees would be different.Objective:There are methods by which biologists summarize different phylogenetic trees to a tree, called consensus tree. A consensus method deals with the combination of gene trees to estimate a species tree. As the phylogenetic trees grow and their number is increased, estimating a consensus tree based on the species-level phylogenetic trees becomes a challenge.Methods:The current study aims at using the Imperialist Competitive Algorithm (ICA) to estimate bifurcating consensus trees. Evolutionary algorithms like ICA are suitable to resolve problems with the large space of candidate solutions.Results:The obtained consensus tree has more similarity to the native phylogenetic tree than related studies.Conclusion:The proposed method enjoys mechanisms and policies that enable us more than other evolutionary algorithms in tuning the proposed algorithm. Thanks to these policies and the mechanisms, the algorithm enjoyed efficiently in obtaining the optimum consensus tree. The algorithm increased the possibility of selecting an optimum solution by imposing some changes in its parameters.
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Gao, Mingan, Zhiyuan Wang, and Gehao Lu. "Enhancing Consensus Security and Privacy with Multichain Ring Signatures Based on HotStuff." Electronics 12, no. 22 (November 13, 2023): 4632. http://dx.doi.org/10.3390/electronics12224632.
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The paper introduces a novel consensus algorithm named MRPBFT, which is derived from the HotStuff consensus protocol and improved upon to address security deficiencies in traditional consensus algorithms within the domain of digital asset transactions. MRPBFT aims to enhance security and privacy protection while pursuing higher consensus efficiency. It employs a multi-primary-node approach and a ring signature mechanism to reinforce security and privacy preservation features in the consensus system. This algorithm primarily focuses on two main improvements: Firstly, it proposes the ed25519LRS signature algorithm and discusses its anonymity for transaction participants and the non-forgeability of signature information in the identity verification and message verification processes within the consensus algorithm. Secondly, the paper introduces MPBFT asynchronous view changes and a multi-primary-node mechanism to enhance consensus efficiency, allowing for view switching in the absence of global consensus. With the introduction of the multi-primary-node mechanism, nodes can be flexibly added or removed, supporting parallel processing of multiple proposals and transactions. Finally, through comparative experiments, the paper demonstrates that the improved algorithm performs significantly better in terms of throughput and network latency.
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Lu, Shaofei, Xuyang Zhang, Renke Zhao, Lizhi Chen, Junyi Li, and Guanzhong Yang. "P-Raft: An Efficient and Robust Consensus Mechanism for Consortium Blockchains." Electronics 12, no. 10 (May 17, 2023): 2271. http://dx.doi.org/10.3390/electronics12102271.
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With the rise in blockchain technology, consortium blockchains have garnered increasing attention in practical applications due to their decentralization and immutability. However, the performance of current consortium blockchains remains a significant obstacle to large-scale commercial adoption. The consensus algorithm, as a fundamental component of blockchain technology, plays a critical role in ensuring both security and efficiency. Unfortunately, most existing consensus algorithms for consortium blockchains are vote-based consensus algorithms, and the performance of vote-based consensus algorithms is largely limited by the performance of the leader node. Therefore, we present P-Raft: a high-performance consensus algorithm that builds upon the Raft algorithm and leverages node server performance evaluations. The primary objectives of this article included enhancing the efficiency of Leader processing, promoting the utilization of the consortium blockchain, and ensuring the robustness of Leader election. Specifically designed to meet the service requirements of consortium blockchain’s consensus mechanism, the P-Raft incorporated the Yasa model, which evaluated the instant machine performance of each node. The performance of each node is then associated with the election timeout, ensuring that nodes with superior performance are more likely to be chosen as Leaders. Additionally, we implemented a leader verification mechanism based on the Bohen-Lynn-Shacham (BLS) signature, which prevented malicious Byzantine nodes from becoming Leaders without receiving enough votes. Empirical findings show that the P-Raft can swiftly designate high-performing nodes as Leaders, thereby greatly improving service efficiency in the consensus process and the overall performance of the consensus mechanism. Ultimately, P-Raft is better equipped to meet the demands of consortium blockchain applications for large-scale transactions.
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Petrescu, M., and R. Petrescu. "Log Replication in Raft vs Kafka." Studia Universitatis Babeș-Bolyai Informatica 65, no. 2 (December 12, 2020): 66. http://dx.doi.org/10.24193/subbi.2020.2.05.
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The implementation of a fault-tolerant system requires some type of consensus algorithm for correct operation. From Paxos to View-stamped Replication and Raft multiple algorithms have been developed to handle this problem. This paper presents and compares the Raft algorithm and Apache Kafka, a distributed messaging system which, although at a higher level, implements many concepts present in Raft (strong leadership, append-only log, log compaction, etc.).This shows that mechanisms conceived to handle one class of problems (consensus algorithms) are very useful to handle a larger category in the context of distributed systems.
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Yan, Jingdong, and Wuwei Liu. "An Ensemble Clustering Approach (Consensus Clustering) for High-Dimensional Data." Security and Communication Networks 2022 (May 16, 2022): 1–9. http://dx.doi.org/10.1155/2022/5629710.
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Due to the plurality of irrelevant attributes, sparse distribution, and complicated calculations in high-dimensional data, traditional clustering algorithms, such as K-means, do not perform well on high-dimensional data. To address the clustering problem of high-dimensional data, this paper studies an integrated clustering method for high-dimensional data. A method of subspace division based on minimum redundancy is proposed to solve the problem of subspace division of high-dimensional data; subspace division is improved by using the K-means algorithm. Additionally, this method uses mutual information between the characteristic variables of the data to replace the calculation in the K-means algorithm. The distance between the characteristic variables of the data is used to divide the data into subspaces according to the mutual information values between the characteristic variables of the data. To achieve high clustering accuracy and diversity based on clustering requirements, this paper uses a genetic algorithm as the consistency integration function. The fitness function is designed according to the clustering fusion target, and the selection operator is designed according to the maximum number of overlapping elements in the base clustering. The experimental results show that the clustering algorithm proposed in this paper outperforms other methods on most datasets and is an effective clustering integration algorithm. The proposed clustering algorithm is compared with other commonly used clustering fusion algorithms on datasets to prove the advantages of the proposed algorithm.
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Jiang, Zhenni, and Xiyu Liu. "A Novel Consensus Fuzzy K-Modes Clustering Using Coupling DNA-Chain-Hypergraph P System for Categorical Data." Processes 8, no. 10 (October 21, 2020): 1326. http://dx.doi.org/10.3390/pr8101326.
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In this paper, a data clustering method named consensus fuzzy k-modes clustering is proposed to improve the performance of the clustering for the categorical data. At the same time, the coupling DNA-chain-hypergraph P system is constructed to realize the process of the clustering. This P system can prevent the clustering algorithm falling into the local optimum and realize the clustering process in implicit parallelism. The consensus fuzzy k-modes algorithm can combine the advantages of the fuzzy k-modes algorithm, weight fuzzy k-modes algorithm and genetic fuzzy k-modes algorithm. The fuzzy k-modes algorithm can realize the soft partition which is closer to reality, but treats all the variables equally. The weight fuzzy k-modes algorithm introduced the weight vector which strengthens the basic k-modes clustering by associating higher weights with features useful in analysis. These two methods are only improvements the k-modes algorithm itself. So, the genetic k-modes algorithm is proposed which used the genetic operations in the clustering process. In this paper, we examine these three kinds of k-modes algorithms and further introduce DNA genetic optimization operations in the final consensus process. Finally, we conduct experiments on the seven UCI datasets and compare the clustering results with another four categorical clustering algorithms. The experiment results and statistical test results show that our method can get better clustering results than the compared clustering algorithms, respectively.
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Yang, Chun-xi, Wei-xing Hong, Ling-yun Huang, and Hua Wang. "Fast Consensus Tracking of Multiagent Systems with Diverse Communication Delays and Input Delays." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/253806.
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The consensus tracking problem for discrete-time multiagent systems with input and communication delays is studied. A sufficient condition is obtained over a directed graph based on the frequency-domain analysis. Furthermore, a fast decentralized consensus tracking conditions based on incrementPIDalgorithm are discussed for improving convergence speed of the multiagent systems. Based on this result, genetic algorithm is introduced to construct incrementPIDbased on genetic algorithm for obtaining optimization consensus tracking performance. Finally, a numerable example is given to compare convergence speed of three tracking algorithms in the same condition. Simulation results show the effectiveness of the proposed algorithm.
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Perelman, B. S., A. W. Evans, and K. E. Schaefer. "Mental Model Consensus and Shifts During Navigation System-Assisted Route Planning." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1183–87. http://dx.doi.org/10.1177/1541931213601779.
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A major barrier to effective spatial decision-making in human-agent teams is that humans and algorithms use different mechanisms to solve spatial problems, frequently leading them to produce different solutions. Incongruity between algorithm-generated solutions and human spatial mental models results in higher workload in mixed-initiative systems, and potential breakdowns in trust and team situation awareness. Although these performance effects are well-understood, few methods exist for quantifying and comparing human spatial mental models and algorithm-generated solutions. To address these problems, 27 participants completed solutions to 5 spatial planning problems, before and after receiving assistance from 2 navigation algorithms. A novel path mapping and clustering approach provided a means of quantifying consensus in human mental models, and shifts in those mental models after viewing the algorithm-suggested routes. Human solutions clustered into a small number of shared mental models. Individual differences in trust in each algorithm predicted acceptance of that algorithm’s route.
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Jiang, Wangxi, Xiaoxiong Wu, Mingyang Song, Jiwei Qin, and Zhenhong Jia. "Improved PBFT Algorithm Based on Comprehensive Evaluation Model." Applied Sciences 13, no. 2 (January 13, 2023): 1117. http://dx.doi.org/10.3390/app13021117.
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Blockchain technology is well known due to the advent of Bitcoin. With the development of recent years, blockchain technology has been widely used in medicine, digital currency, energy, etc. The practical Byzantine fault-tolerant (PBFT) algorithm is a consensus algorithm widely used in consortium blockchains. Aiming to address the problems of the PBFT algorithm, low consensus efficiency due to high communication complexity, and malicious behavior of the primary node leading to consensus failure, an improved PBFT algorithm based on a comprehensive evaluation model (TB-PBFT) is proposed. First, nodes are divided into several groups based on the multi-formation control strategy of an unmanned aerial vehicle (UAV) cluster, which significantly reduces the communication complexity. Second, a comprehensive evaluation model combining the entropy method, TOPSIS method, and Borda count is proposed, which uses the behavior of nodes as an evaluation index, and the comprehensive score of nodes is obtained according to the preferences of other nodes. Finally, the highest ranking node is selected as the primary node through the comprehensive evaluation model to ensure the security and stability of the blockchain network. We analyze TB-PBFT algorithms and compare them with other Byzantine fault tolerance algorithms. Theoretical analysis and simulation results show that the TB-PBFT algorithm can improve node scalability and fault tolerance and reduce communication complexity and view switching probability. We also prove that the comprehensive evaluation model can improve the consensus success rate of the algorithm, and the feasibility and effectiveness of the improved consensus algorithm are verified. Hence, it can be applied to the consortium blockchain system effectively and efficiently.
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Patil, Vaibhav Nivrutti, and Vijay H. Kalmani. "Enhancing security and ensuring secure performance: A performance evaluation of consensus algorithms in a distributed healthcare blockchain system." Journal of Statistics and Management Systems 26, no. 6 (2023): 1391–406. http://dx.doi.org/10.47974/jsms-1079.
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Blockchain is an emerging technology in today’s real-time applications and database transaction systems—the primary motto is to determine transactional clarity to end-user without any fluctuation. According to the basic block policy, it is immutable or does not allow updating the existing transaction, which automatically maintains the security and transaction clarity. This paper proposes a system performance evaluation of various consensus algorithms in a distributed environment with a peer-to-peer network. The four different consensus algorithms have been evaluated in four peer nodes. Healthcare application has been successfully tested with the entire system. The first blockchain implementation has done in a Java environment with the custom hash generation, mining strategy, and smart contract for each level. Each algorithm provides different time complexity accordingly. The system evaluates the performance of four consensus algorithms sequentially and demonstrates the effectiveness and utilization of each algorithm according to the requirements.
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Bauer, V. P., and V. V. Smirnov. "Institutional Features of the Development of Competitive Cryptocurrency." Finance: Theory and Practice 24, no. 5 (October 24, 2020): 84–99. http://dx.doi.org/10.26794/2587-5671-2020-24-5-84-99.
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The aim of the article is to clarify the basics of the digitalization strategy of the competitive businesses and identify features of the institutional environment that ensure the development of cryptocurrency as a new asset (IT product) of the modern economy, analyze the methods of implementing the cryptocurrency business models. The relevance of the research paper is determined by the need to develop a competitive Russian cryptocurrency (including the cryptoruble) with the growing private, state and cross-national cryptocurrencies. The scientific novelty of the study implies clarifying the informal and formal rules of the institutional environment and related methods ensuring the development of a competitive cryptocurrency. The authors consider the following methods to implement the institutional features of the cryptocurrencies business model development: logic and blockchain algorithm that establish trust and collaboration between cryptocurrency developers; logic and blockchain consensus algorithm ensuring that all the parties of the blockchain network come to a common agreement (consensus); logic and blockchain algorithms that form cryptocurrency transactions and control its turnover by generating blocks of cryptocurrencies, by forming the structure of blocks and transactions of cryptocurrencies, by storing cryptocurrencies’ keys and providing security, by mining (forging) cryptocurrency, etс.The results of the study provide a basis for identifying the institutional features and the corresponding methods providing a competitive cryptocurrency development with a detailed analysis of the blockchain consensus algorithms that ensure the competitiveness of the cryptocurrency. The conclusions show that the most promising are the hybrid consensus algorithms which may include both the logic of two or more known algorithms and the original logic of a new algorithm. The authors recommend defining the logic of the blockchain consensus algorithm as a priority when developing a cryptocurrency to ensure reliability of the transactions in the blockchain network, thus increasing the competitiveness of the cryptocurrency.
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Liu, Wei, Xuhao Zhang, Wenlong Feng, Mengxing Huang, and Yun Xu. "Optimization of PBFT Algorithm Based on QoS-Aware Trust Service Evaluation." Sensors 22, no. 12 (June 17, 2022): 4590. http://dx.doi.org/10.3390/s22124590.
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In service-transaction scenarios, blockchain technology is widely used as an effective tool for establishing trust between service providers and consumers. The consensus algorithm is the core technology of blockchain. However, existing consensus algorithms, such as the practical Byzantine fault tolerance (PBFT) algorithm, still suffer from high resource consumption and latency. To solve this problem, in this study, we propose an improved PBFT blockchain consensus algorithm based on quality of service (QoS)-aware trust service evaluation for secure and efficient service transactions. The proposed algorithm, called the QoS-aware trust practical Byzantine fault tolerance (QTPBFT) algorithm, efficiently achieves consensus, significantly reduces resource consumption, and enhances consensus efficiency. QTPBFT incorporates a QoS-aware trust service global evaluation mechanism that implements service reliability ranking by conducting a dynamic evaluation according to the real-time performance of the services. To reduce the traffic of the blockchain, it uses a mechanism that selects nodes with higher values to form a consensus group that votes for consensus according to the global evaluation result of the trust service. A practical protocol is also constructed for the proposed algorithm. The results of extensive simulations and comparison with other schemes verify the efficacy and efficiency of the proposed scheme.
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Kenyeres, Martin, and Jozef Kenyeres. "Comparative Study of Distributed Consensus Gossip Algorithms for Network Size Estimation in Multi-Agent Systems." Future Internet 13, no. 5 (May 18, 2021): 134. http://dx.doi.org/10.3390/fi13050134.
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Determining the network size is a critical process in numerous areas (e.g., computer science, logistic, epidemiology, social networking services, mathematical modeling, demography, etc.). However, many modern real-world systems are so extensive that measuring their size poses a serious challenge. Therefore, the algorithms for determining/estimating this parameter in an effective manner have been gaining popularity over the past decades. In the paper, we analyze five frequently applied distributed consensus gossip-based algorithms for network size estimation in multi-agent systems (namely, the Randomized gossip algorithm, the Geographic gossip algorithm, the Broadcast gossip algorithm, the Push-Sum protocol, and the Push-Pull protocol). We examine the performance of the mentioned algorithms with bounded execution over random geometric graphs by applying two metrics: the number of sent messages required for consensus achievement and the estimation precision quantified as the median deviation from the real value of the network size. The experimental part consists of two scenarios—the consensus achievement is conditioned by either the values of the inner states or the network size estimates—and, in both scenarios, either the best-connected or the worst-connected agent is chosen as the leader. The goal of this paper is to identify whether all the examined algorithms are applicable to estimating the network size, which algorithm provides the best performance, how the leader selection can affect the performance of the algorithms, and how to most effectively configure the applied stopping criterion.