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consensus algorithms in Blockchain-Based Cryptocurrencies

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Consensus Algorithms in Blockchain-Based Cryptocurrencies

Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Rameez Yousuf Zubair Jeelani Dawood Ashraf Khan Owais Bhat Tawseef Ahmed Teli University of Kashmir J&K India Islamic University of Science and Technology J&K India Cluster University Srinagar J&K India

ISBN: (数字)9781728157917

ISBN: (纸本)9781728157924

Blockchain has been a breakthrough in the technology since the last decade and is anticipated as the go-to thing due to features presented by it. The features such as secure, immutable, transparent, and anonymous makes Blockchain technology the frontrunner in the untrustworthy distributed environment. The driving force behind the Blockchain technology are the consensus algorithms that are at the heart of any Blockchain technology. These algorithms determine the security and performance of any Blockchain. The most popular consensus algorithm is the Proof-of-Work which was first used in the Bitcoin. Since then, a number of consensus algorithms have been proposed. This paper presents a brief overview of the Blockchain Technology and popular cryptocurrencies based on Blockchain. Next, the most popular consensus algorithms in the context of Blockchain and cryptocurrencies are discussed.

关键词： Heart Force Blockchain consensus algorithm Bitcoin Cryptography Reliability

A survey of Blockchain consensus algorithms:mechanism, design and applications

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Science China(Information Sciences) 2021年第2期64卷 100-114页

作者： Xiang FU Huaimin WANG Peichang SHI College of Computer National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology

In 2008, Blockchain was introduced to the world as the underlying technology of the Bitcoin system. After more than a decade of development, various Blockchain systems have been proposed by both academia and industry. This paper focuses on the consensus algorithm, which is one of the core technologies of Blockchain. In this paper, we propose a unified consensus algorithm process model that is suitable for Blockchains based on both the chain and directed acyclic graph(DAG) structure. Subsequently, we analyze various mainstream Blockchain consensus algorithms and classify them according to their design in different phases of the process model. Additionally, we present an evaluation framework of Blockchain consensus algorithms and then discuss the security design principles that enable resistance from different ***, we provide some suggestions for selecting consensus algorithms in different Blockchain application scenarios.

关键词： Blockchain consensus algorithm Byzantine fault-tolerant process model design principles

Shapley-Based Feature Selection for Online algorithm Selection

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Shapley-Based Feature Selection for Online Algorithm Select...

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023

作者： Becker, Patrick Bengs, Viktor Munich Germany Munich Germany Munich Germany

ISBN: (纸本)9783031746291

Online algorithm selection concerns the task of designing a dynamic algorithm selector that observes sequentially arriving problem instances of an algorithmic problem class for which it must select a suitable algorithm from a given pool of candidate algorithms. Typically the suitability of a candidate algorithm is determined by its average runtime for solving a problem instance. Recent work has shown that multi-armed bandit algorithms can be leveraged for specifying a suitable algorithm selector by taking available feature information of problem instances into account. In this paper, we investigate whether the performance of these bandit-based selection strategies can be further improved by incorporating feature selection. To this end, we use the concept of Shapley values from cooperative game theory to specify the contribution of the features with respect to the suitability of the candidate algorithms and adapt the bandit-based selection strategies to consider only features with the highest contribution. We present two different Shapley value-based approaches and show empirically that UCB-based bandit selection strategies can be improved, while Thompson sampling-based strategies actually deteriorate in terms of average runtime. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： consensus algorithm

Stochastic Parareal algorithm for Stochastic Differential Equations

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arXiv 2025年

作者： Wang, Huanxin Lyu, Junhan Peng, Zicheng Li, Min School of Mathematics and Physics China University of Geosciences Wuhan430074 China School of Business Hong Kong Baptist University Kowloon Tong Hong Kong School of Business Macau University of Science and Technology 999078 China School of Mathematics and Physics Center for Mathematical Sciences China University of Geosciences Wuhan430074 China

This paper analyzes the SParareal algorithm for stochastic differential equations (SDEs). Compared to the classical Parareal algorithm, the SParareal algorithm accelerates convergence by introducing stochastic perturbations, achieving linear convergence over unbounded time intervals. We first revisit the classical Parareal algorithm and stochastic Parareal algorithm. Then we investigate mean-square stability of the SParareal algorithm based on the stochastic θ-method for SDEs, deriving linear error bounds under four sampling rules. Numerical experiments demonstrate the superiority of the SParareal algorithm in solving both linear and nonlinear SDEs, reducing the number of iterations required compared to the classical Parareal algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： consensus algorithm

Greedy algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure

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arXiv 2025年

作者： Slivkins, Aleksandrs Xu, Yunzong Zuo, Shiliang Microsoft Research New York City United States University of Illinois Urbana-Champaign United States

We study the greedy (exploitation-only) algorithm in bandit problems with a known reward structure. We allow arbitrary finite reward structures, while prior work focused on a few specific ones. We fully characterize when the greedy algorithm asymptotically succeeds or fails, in the sense of sublinear vs. linear regret as a function of time. Our characterization identifies a partial identifiability property of the problem instance as the necessary and sufficient condition for the asymptotic success. Notably, once this property holds, the problem becomes easy—any algorithm will succeed (in the same sense as above), provided it satisfies a mild non-degeneracy condition. We further extend our characterization to contextual bandits and interactive decision-making with arbitrary feedback, and demonstrate its broad applicability across various examples. Copyright © 2025, The Authors. All rights reserved.

关键词： consensus algorithm

THE BEST TWO-TERM UNDERAPPROXIMATION USING NUMBERS FROM FIBONACCI-TYPE SEQUENCES

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arXiv 2025年

作者： Mark, Shiliaev Department of Mathematics Texas A&M University College StationTX77843 United States

This paper studies the greedy two-term underapproximation of θ ∈ (0, 1] using reciprocals of numbers from a Fibonacci-type sequence (Equation presented). We find the set of θ whose greedy two-term underapproximation is the best among all two-term underapproximations using 1/cn's. We then derive a neat description of the set when (Equation presented) is the Fibonacci sequence or the Lucas *** Codes 11A67, 11B99 © 2025, CC BY.

关键词： consensus algorithm

An adaptive forward-backward-forward splitting algorithm for solving pseudo-monotone inclusions

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arXiv 2025年

作者： Chorobura, Flavia Necoara, Ion Pesquet, Jean-Christophe Automatic Control and Systems Engineering Department National University of Science and Technology Politehnica Bucharest Bucharest060042 Romania Federal Institute of Education Science and Technology of Paraná campus Foz do Iguaçu Brazil Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest050711 Romania University Paris-Saclay CentraleSupélec CVN Inria Gif-sur-Yvette France

In this paper, we propose an adaptive forward-backward-forward splitting algorithm for finding a zero of a pseudo-monotone operator which is split as a sum of three operators: the first is continuous single-valued, the second is Lipschitzian, and the third is maximally monotone. This setting covers, in particular, constrained minimization scenarios, such as problems having smooth and convex functional constraints (e.g., quadratically constrained quadratic programs) or problems with a pseudo-convex objective function minimized over a simple closed convex set (e.g., quadratic over linear fractional programs). For the general problem, we design a forward-backward-forward splitting type method based on novel adaptive stepsize strategies. Under an additional generalized Lipschitz property of the first operator, sublinear convergence rate is derived for the sequence generated by our adaptive algorithm. Moreover, if the sum is uniformly pseudo-monotone, linear/sublinear rates are derived depending on the parameter of uniform pseudo-monotonicity. Preliminary numerical experiments demonstrate the good performance of our method when compared to some existing optimization methods and software. © 2025, CC BY.

关键词： consensus algorithm

A declarative approach to specifying distributed algorithms using three-valued modal logic

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arXiv 2025年

作者： Gabbay, Murdoch J. Zanolini, Luca Heriot-Watt University Edinburgh United Kingdom Ethereum Foundation London United Kingdom

We present Coalition Logic, a three-valued modal fixed-point logic designed for declaratively specifying and reasoning about distributed algorithms, such as the Paxos consensus algorithm. Our methodology represents a distributed algorithm as a logical theory, enabling correctness properties to be derived directly within the framework—or revealing logical errors in the algorithm’s design when they exist. Coalition Logic adopts a declarative approach, specifying the overall logic of computation without prescribing control flow. Notably, message-passing is not explicitly modeled, distinguishing our framework from approaches like TLA+. This abstraction emphasises the logical essence of distributed algorithms, offering a novel perspective on their specification and reasoning. We define the syntax and semantics of Coalition Logic, explore its theoretical properties, and demonstrate its applicability through a detailed treatment of the Paxos consensus algorithm. By presenting Paxos as a logical theory and deriving its standard correctness properties, we showcase the framework’s capacity to handle non-trivial distributed systems. We envision Coalition Logic as a versatile tool for specifying and reasoning about distributed algorithms. The Paxos example highlights the framework’s ability to capture intricate details, offering a new lens through which distributed algorithms can be specified, studied, and *** Codes 03B45, 03B50, 68Q60 © 2025, CC BY.

关键词： consensus algorithm

Convergence analysis for a variant of manifold proximal point algorithm based on Kurdyka-Lojasiewicz property

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arXiv 2025年

作者： Yu, Peiran Zeng, Liaoyuan Pong, Ting Kei Department of Computer Science The University of Maryland United States School of Mathematical Sciences Zhejiang University of Technology China Department of Applied Mathematics The Hong Kong Polytechnic University Hong Kong

We incorporate an iteratively reweighted strategy in the manifold proximal point algorithm (ManPPA) in [12] to solve an enhanced sparsity inducing model for identifying sparse yet nonzero vectors in a given subspace. We establish the global convergence of the whole sequence generated by our algorithm by assuming the Kurdyka-Ĺojasiewicz (KL) properties of suitable potential functions. We also study how the KL exponents of the different potential functions are related. More importantly, when our enhanced model and algorithm reduce, respectively, to the model and ManPPA with constant stepsize considered in [12], we show that the sequence generated converges linearly as long as the optimal value of the model is positive, and converges finitely when the limit of the sequence lies in a set of weak sharp minima. Our results improve [13, Theorem 2.4], which asserts local quadratic convergence in the presence of weak sharp minima when the constant stepsize is small. Copyright © 2025, The Authors. All rights reserved.

关键词： consensus algorithm