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26th International Symposium on Formal Methods (FM)

作者： Baumeister, Tom Eichler, Paul Jacobs, Swen Sakr, Mouhammad Volp, Marcus CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Luxembourg Univ SnT Esch Sur Alzette Luxembourg

ISBN: (纸本)9783031711619;9783031711626

Threshold automata are a computational model that has proven to be versatile in modeling threshold-based distributed algorithms and enabling their completely automatic parameterized verification. We present novel techniques for the verification of threshold automata, based on well-structured transition systems, that allow us to extend the expressiveness of both the computational model and the specifications that can be verified. In particular, we extend the model to allow decrements and resets of shared variables, possibly on cycles, and the specifications to general coverability. While these extensions of the model in general lead to undecidability, our algorithms provide a semi-decision procedure. We demonstrate the benefit of our extensions by showing that we can model complex round-based algorithms such as the phase king consensus algorithm and the Red Belly Blockchain protocol (published in 2019), and verify them fully automatically for the first time.

关键词： consensus algorithm

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Trusted-Region Subsequence Reduction for Designing Resilient consensus algorithms

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2021年第1期8卷 259-268页

作者： Zhai, Yang Liu, Zhi-Wei Ge, Ming-Feng Wen, Guanghui Yu, Xinghuo Qin, Yuzhen Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China China Univ Geosci Sch Mech Engn & Elect Informat Wuhan 430074 Peoples R China Southeast Univ Dept Syst Sci Sch Math Nanjing 211189 Peoples R China RMIT Univ Sch Engn Melbourne Vic 3001 Australia Univ Calif Riverside Dept Mech Engn Riverside CA 92521 USA

Existing resilient consensus algorithms are mainly developed based on the mean subsequence reduced (MSR) method, which relies on the assumption that there exist at most f malicious agents in the entire network or each neighborhood (i.e., f-total or f-local model). However, in some practical cases, it may be impossible to estimate an appropriate upper bound on the number of malicious agents. This paper proposes a novel method, called trusted-region subsequence reduction (TSR), for designing resilient consensus algorithm without the f-total/local model assumption. The main idea of the TSR method is to filter out the received information beyond a dynamic trusted region, determined by the current relative positions of the neighboring trusted nodes. Based on the TSR method, we design a sampled-data resilient consensus algorithm for double-integrator multi-agent networks. A necessary and sufficient graph-theoretic condition is obtained to achieve resilient consensus. Finally, simulations are conducted to illustrate the effectiveness of the proposed algorithm and the faster convergence rate of the TSR-based algorithm than the classical MSR-based algorithm.

关键词： consensus algorithm Topology Convergence Germanium Upper bound Task analysis Mechanical engineering Multi-agent network resilient consensus malicious attack trusted-region subsequence reduction

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algorithm-Level Confidentiality for Average consensus on Time-Varying Directed Graphs

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2022年第2期9卷 918-931页

作者： Gao, Huan Wang, Yongqiang Northwestern Polytech Univ Sch Automat Xian 710129 Peoples R China Clemson Univ Dept Elect & Comp Engn Clemson SC 29634 USA

Average consensus plays a key role in distributed networks, with applications ranging from time synchronization, information fusion, load balancing, to decentralized control. Existing average consensus algorithms require individual agents to exchange explicit state values with their neighbors, which leads to the undesirable disclosure of sensitive information in the state. In this paper, we propose a novel average consensus algorithm for time-varying directed graphs that can protect the confidentiality of a participating agent against other participating agents. The algorithm injects randomness in interaction to obfuscate information on the algorithm-level and can ensure information-theoretic privacy without the assistance of any trusted third party or data aggregator. By leveraging the inherent robustness of consensus dynamics against random variations in interaction, our proposed algorithm can also guarantee the accuracy of average consensus. The algorithm is distinctly different from differential-privacy based average consensus approaches which enable confidentiality through compromising accuracy in obtained consensus value. Numerical simulations confirm the effectiveness and efficiency of our proposed approach.

关键词： Directed graphs Heuristic algorithms Network topology consensus algorithm Topology Synchronization Privacy Average consensus confidentiality time-varying directed graphs

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Dynamic Independent Set of Disks (and Hypercubes) Made Easier 8

Dynamic Independent Set of Disks (and Hypercubes) Made Easie...

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8th SIAM Symposium on Simplicity of algorithms, SOSA 2025

作者： Bhore, Sujoy Chan, Timothy M. Department of Computer Science & Engineering Indian Institute of Technology Bombay Mumbai India Department of Computer Science University of Illinois Urbana-Champaign United States

ISBN: (纸本)9781611978315

Maintaining an approximate maximum independent set of a dynamic collection of objects has been studied extensively in the past few years. Recently, Bhore, Nöllenburg, Tóth, and Wulms (SoCG 2024) showed that for (unweighted) disks in the plane, it is possible to maintain O(1)-factor approximate solution in polylogarithmic amortized update time. In this work, we provide a much simpler dynamic O(1)-approximation algorithm, which at the same time improves the number of logarithmic factors in the previous update time bound. Along the way, we also obtain simpler and faster algorithms for dynamic independent set for axis-aligned hypercubes as well as static independent set for fat objects in any constant dimension. All the above results also hold for the minimum piercing set problem for the same classes of objects. Copyright © 2025 Copyright for this paper is retained by authors.

关键词： consensus algorithm

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Posterior Tracking algorithm for Multi-objective Classification Bandits 37th

Posterior Tracking Algorithm for Multi-objective Classifica...

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37th Australasian Joint Conference on Artificial Intelligence, AJCAI 2024

作者： Suzuki, Riku Nakamura, Atsuyoshi Graduate School of Information Science and Technology Hokkaido University Sapporo Japan

ISBN: (纸本)9789819603503

A classification bandit problem is a kind of pure exploration K-armed bandit problems in which a given set of K arms must be judged whether it contains at least L good arms or not with probability at least 1-δ for a given positive integer L(≤K) and δ>0, by drawing as small number of arms as possible, where an arm is good if and only if its expected reward μ is at least a given threshold ξ. To apply algorithms for this problem to more diverse real-world problems, we extend the problem with one dimensional rewards to that with multi-dimensional rewards by defining good arms as arms whose i-th dimensional expected reward μi is at least given threshold ξi for all the dimensions i. We also extend P-Tracking algorithm, which is reported to be a best performer for the original one-dimensional-reward problem, to that for our multi-dimensional-reward problem. Our results using numerical simulations demonstrate the superiority of the extended P-Tracking algorithm in sample efficiency compared to extended other existing algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： consensus algorithm

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A Comparative Analysis of consensus algorithms for Decentralized Storage Systems

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IT PROFESSIONAL 2022年第6期24卷 59-65页

作者： Sharma, Pratima Jindal, Rajni Borah, Malaya Dutta Bennett Univ Greater Noida 201310 Uttar Pradesh India Delhi Technol Univ Delhi 110042 India Natl Inst Technol Silchar Silchar 788010 Assam India

Blockchain has emerged as a revolutionary technology for various industrial applications of the next century. One of them is a decentralized storage system enabled by the corporation of Blockchain technology. In this context, Blockchain provides innovation to address traditional storage challenges by securely transmitting files through a fully decentralized network and eliminating the data failure risks that arise from a centralized structure. The decentralized storage system allows people to rent out unused hardware storage space and must prove that they store unaltered files. This study gives general readers an overview of decentralized storage technologies in various aspects, including background and technical details. Then, we explore the different consensus protocols used in the decentralized storage system. Finally, we discuss the various aspects of the Blockchain-based decentralized storage system.

关键词： Technological innovation Costs consensus algorithm Hardware Blockchains consensus protocol Security

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Resource Analysis of Blockchain consensus algorithms in Hyperledger Fabric

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IEEE ACCESS 2022年 10卷 74902-74920页

作者： Yang, Gyeongsik Lee, Kwanhoon Lee, Kyungwoon Yoo, Yeonho Lee, Hyowon Yoo, Chuck Korea Univ Dept Comp Sci & Engn Seoul 02841 South Korea Kyungpook Natl Univ Sch Elect Engn Daegu 41566 South Korea

In the blockchain network, the consensus algorithm is used to tolerate node faults with data consistency and integrity, so it is vital in all blockchain services. Previous studies on the consensus algorithm have the following limitations: 1) no resource consumption analysis was done, 2) performance analysis was not comprehensive in terms of blockchain parameters (e.g., number of orderer nodes, number of fault nodes, batch size, payload size), and 3) practical fault scenarios were not evaluated. In other words, the resource provisioning of consensus algorithms in clouds has not been addressed adequately. As many blockchain services are deployed in the form of blockchain-as-a-service (BaaS), how to provision consensus algorithms becomes a key question to be answered. This study presents a kernel-level analysis for the resource consumption and comprehensive performance evaluations of three major consensus algorithms (i.e., Kafka, Raft, and PBFT). Our experiments reveal that resource consumption differs up to seven times, which demonstrates the importance of proper resource provisioning for BaaS.

关键词： Peer-to-peer computing consensus algorithm Fabrics Distributed ledger Blockchains Proposals Throughput Blockchain blockchain-as-a-service cloud consensus algorithm hyperledger fabric performance analysis Kafka Raft PBFT Microsoft Azure AWS

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consensus of Multi-Agent Systems Under Binary-Valued Measurements and Recursive Projection algorithm

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2020年第6期65卷 2678-2685页

作者： Wang, Ting Zhang, Hang Zhao, Yanlong Chinese Acad Sci Acad Math & Syst Sci Inst Syst Sci Key Lab Syst & Control Beijing 100190 Peoples R China

This paper studies consensus problems of multi-agent systems with binary-valued communications. Different from most existing works, the agents considered in this paper can only get binary-valued observations of its neighbors' states with random noises. A consensus algorithm is proposed: first, each agent estimates its neighbors' states by the recursive projection algorithm;then, each agent designs the control timely based on the estimates. It is proved that the estimates of the states can converge to the true states with a faster convergence rate than that in the parameter estimation. Moreover, the states of the agents can achieve mean-square consensus, and the corresponding consensus speed can achieve O(1/t) under certain conditions. Finally, simulations are given to demonstrate the theoretical results.

关键词： Convergence consensus algorithm Projection algorithms Noise measurement Estimation Multi-agent systems Approximation algorithms Binary-valued communications convergence convergence rate consensus control estimate multi-agent systems recursive projection algorithm

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An In-Label Prioritizing Variable Branching Strategy of SAT Solvers for a Preferred Extension of Argumentation Frameworks 21st

An In-Label Prioritizing Variable Branching Strategy of SAT...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Luo, Mao Xiong, Jiao He, Ningning Xiong, Caiquan Wu, Xinyun Wu, Jun Hubei University of Technology Wuhan430068 China Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789819601271

The SAT-based reduction methods have shown significant effectiveness in solving preferred extensions problem in argumentation frameworks. As a general-purpose solver, SAT solvers does not fully utilize the inherent properties of argumentation framework problems for customized design, resulting in suboptimal performance. Therefore, this paper proposes an in-label prioritizing variable branching strategy to improve the SAT solver from two aspects: the initialization of the polarity values of decision variables and the evaluation criteria for variable’s activity, enabling efficient solving of a preferred extension of argumentation frameworks. We implement this method in the state-of-the-art argumentation algorithm ArgSemSAT and conducted experimental analysis using the internationally recognized benchmarks ICCMA 2023 and ICCMA 2021. The experimental results show that the proposed method significantly enhances the performance of the original algorithm in solving a preferred extension, increasing the proportion of instances solved by the original algorithm by 6.96% for ICCMA 2023 and 37.5% for ICCMA 2021. Furthermore, the optimized algorithm outperforms μ-toksia (cmsat) which ranks the third-place in the competition ICCMA 2023. Notably, the proposed algorithm demonstrates very efficient performance on the AFGen instances, reducing the average solving time of the original algorithm from 350.88 s to 5.75 s. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： consensus algorithm

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A Simple Parallel algorithm with Near-Linear Work for Negative-Weight Single-Source Shortest Path 8

A Simple Parallel Algorithm with Near-Linear Work for Negati...

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8th SIAM Symposium on Simplicity of algorithms, SOSA 2025

作者： Fischer, Nick Haeupler, Bernhard Latypov, Rustam Roeyskoe, Antti Sulser, Aurelio L. INSAIT Sofia University "St. Kliment Ohridski" Bulgaria ETH Zurich Switzerland Aalto University Finland ETH Zurich Switzerland

ISBN: (纸本)9781611978315

We give the first parallel algorithm with optimal Õ(m) work for the classical problem of computing Single-Source Shortest Paths in general graphs with negative-weight edges. In graphs without negative edges, Dijkstra's algorithm solves the Single-Source Shortest Paths (SSSP) problem with optimal Õ(m) work, but is inherently sequential. A recent breakthrough by [Bernstein, Nanongkai, Wulff-Nilsen;FOCS'22] achieves the same for general graphs. Parallel shortest path algorithms are more difficult and have been intensely studied for decades. Only very recently, multiple lines of research culminated in parallel algorithms with optimal work Õ(m) for various restricted settings, such as approximate or exact algorithms for directed or undirected graphs without negative edges. For general graphs, the best known algorithm by [Ashvinkumar, Bernstein, Cao, Grunau, Haeupler, Jiang, Nanongkai, Su;ESA'24] still requires m1+o(1) work. This paper presents a randomized parallel algorithm for SSSP in general graphs with near-linear work Õ(m) and state-of-the-art span n1/2+o(1). We follow a novel bottom-up approach leading to a particularly clean and simple algorithm. Our algorithm can be seen as a near-optimal parallel black-box reduction from SSSP in general graphs to graphs without negative edges. In contrast to prior works, the reduction in this paper is both parallel and essentially without overhead, only affecting work and span by polylogarithmic factors. Copyright © 2025 Copyright for this paper is retained by authors.

关键词： consensus algorithm

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