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Hierarchical Reputation consensus Model for VANET

IEEE ACCESS 2025年 13卷 3521-3531页

作者： Chen, Ruilong Guan, Yepeng Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China Minist Educ Key Lab Adv Display & Syst Applicat Shanghai 200072 Peoples R China

The vehicular ad hoc network (VANET) enables vehicles to disseminate messages to improve traffic safety and efficiency. However, the task of enabling consensus through synchronous communication among them remains a challenging problem due to the high mobility of vehicles. This prompts the need for a consensus model suitable for VANETs. Thus, A hierarchical reputation consensus model for VANET has been proposed. The model dynamically partitions consensus groups based on vehicles' global reputation, which restricts malicious nodes from participating in consensus to improve consensus efficiency. Secondly, an improved event reliability assessment mechanism is introduced into the reputation model to detect the authenticity of the events and mitigate the fabrication of false events. Finally, a hierarchical directed gossip consensus model based on directed acyclic graph (DAG) called as HDGgraph has been proposed. It is aimed at addressing the challenge of achieving consensus when vehicle communication synchronization cannot be guaranteed. In HDGgraph, vehicles can construct a DAG locally and implement virtual voting to achieve local consensus, which can reduce system communication overhead and significantly improve consensus efficiency. Experimental results demonstrate that our proposed approach outperforms some state-of-the-art methods in terms of performance.

关键词： Reliability consensus protocol Vehicular ad hoc networks Scalability Solid modeling consensus algorithm Vehicle dynamics Peer-to-peer computing Internet of Things Broadcasting DAG blockchain reputation model consensus model hierarchical structure VANET

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Permissioned Blockchain-Based Trusted and Robust consensus Optimization Orienting Intelligent Transportation Systems

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第2期26卷 2011-2026页

作者： Deng, Zhihong Tang, Chunming Li, Taotao He, Debiao Guangzhou Univ Sch Math & Informat Sci Guangzhou 510006 Peoples R China Guangzhou Univ Guangzhou Ctr Appl Math Guangzhou 510006 Peoples R China Guangzhou Univ Key Lab Informat Secur Technol Jointly Guangdong P Guangzhou 510006 Peoples R China Sun Yat Sen Univ Sch Software Engn Zhuhai 528478 Peoples R China Wuhan Univ Sch Cyber Sci & Engn Wuhan 430072 Peoples R China

Efficient and secure data sharing in the Internet of Vehicles (IoV) is critical for the advancement of intelligent transportation, particularly in the context of emerging 5G/6G networks and driverless technology. This has prompted researchers to explore Blockchain-based Internet of Vehicles (BIoV) solutions to address common issues in intelligent transportation systems (ITS). However, at the edge layer, existing reputation and consensus mechanisms in the BIoV model face challenges such as significant energy consumption, limited scalability, and pronounced centralization. To tackle these issues, we introduce TRCO, a Permissioned Blockchain-based Trusted and Robust consensus Optimization orienting ITS. TRCO is a three-layer BIoV architecture applicable to any BIoV scenario, offering robust scalability with the addition of new sub-regions. To improve the quality of data sharing for edge layer, we propose a decentralized reputation evaluation mechanism and integrate PoS and PBFT consensus algorithms to enhance performance by evaluating the communication behavior of edge servers. Security analysis and simulation experiments demonstrate that TRCO achieves high scalability and reliability, effectively filters Byzantine edge servers, and enhances the decentralization and consensus efficiency of the system.

关键词： Servers Trust management Security Scalability Reliability Optimization Transportation consensus algorithm Peer-to-peer computing Filters Permissioned blockchain consensus optimization ITS data sharing scalability

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Improved PBFT consensus Mechanism Based on Voting Sort Clustering Partition With Group Signature for IoT

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第2期26卷 2239-2251页

作者： Dong, Shi Su, Huadong Hou, Ruizhe Shankar, Achyut Zhoukou Normal Univ Sch Comp Sci & Technol Zhoukou 466001 Peoples R China Wuhan Text Univ Sch Comp Sci & Artificial Intelligence Wuhan 430200 Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China Univ Warwick Dept Cyber Syst Engn WMG Coventry CV7 4AL England Graphic Era Deemed Univ Dept Comp Sci & Engn Dehra Dun 248002 India Chandigarh Univ Univ Ctr Res & Dev Mohali 140413 Punjab India Lovely Profess Univ Sch Comp Sci Engn Phagwara 144411 Punjab India Chitkara Univ Ctr Res Impact & Outcome Chandigarh 160002 Punjab India

The consensus mechanism is crucial to blockchain performance, making it essential to design a mechanism that aligns with the characteristics of the Internet of Things (IoT). This paper focuses on the application of PBFT consensus mechanism in the Internet of things. However, it is found that the current PBFT consensus mechanisms need to address some problems, such as communication overhead, bandwidth occupation and privacy protection. In this paper, we propose a voting sorting clustering mechanism based on group signatures to enhance the PBFT consensus mechanism (IPBFT), ensuring privacy protection between Internet of Things nodes. Finally, the communication efficiency is improved. The voting sorting clustering method reduces the communication probability with the nodes, and decreases the communication overhead and bandwidth occupation. Experimental results show that compared with other mechanisms, the proposed mechanism increases throughput, reduces communication overhead and bandwidth occupation, and alleviates privacy protection problems.

关键词： Internet of Things consensus protocol Throughput Fault tolerant systems Fault tolerance Delays consensus algorithm Scalability Protection Clustering algorithms consensus mechanism consortium blockchain PBFT IoT clustering mechanism group signature

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Random cluster parallel PBFT global consensus for consistent blockchain distributed ledger

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2025年第3期28卷 1-19页

作者： Abbessi, Wassim Ouni, Sofiane Othmen, Rabeb Ben Badreddine, Wafa Dequen, Gilles Univ Manouba Natl Comp Sci Sch ENSI CRISTAL Lab RAMSIS Team Campus Univ Manouba 2010 Tunisia Univ Picardie Jules Verne Lab Modelisat Informat Syst MIS F-80080 Amiens France

Blockchain is a distributed ledger that various applications can use to store data in a secure, decentralized, and immutable manner. The key piece in a blockchain is the consensus algorithm that different blockchain nodes run to obtain mutual agreement. While the Practical Byzantine Fault Tolerant (PBFT) is one of the most used algorithms and provides several advantages, it has a high communication cost, and it is executed in a sequential manner for consistency. To improve PBFT for blockchain consensus use, related works have added restrictive assumptions that can compromise security, consistency, and fault tolerance capabilities. This paper proposes a novel parallel PBFT-based consensus algorithm called Random-Cluster parallel PBFT. Our algorithm runs parallel consensus on random clusters in the blockchain network and then the resulting consensus is broadcasted to the blockchain network for a global consensus. Our proposal reduces the communication costs and improves the performance of the consensus which makes the blockchain more scalable. We provide formal proofs of the correctness of our algorithm. We have also proposed an algorithm to resolve the transaction order problem to address a consistent distributed ledger with concurrent consensus. The evaluation of throughput and communication complexity shows that Random-Cluster parallel PBFT provides better performance and more relevant results.

关键词： Lightweight blockchain Parallel PBFT Clustering consensus algorithm

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A Distributed consensus Scenario Approach to Optimization and Control With Uncertainties

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IEEE ACCESS 2025年 13卷 5308-5320页

作者： Wang, Jing Drager, Steven Illinois State Univ Dept Elect Engn Normal IL 61761 USA Air Force Res Lab Rome NY 13441 USA

This paper addresses the problem of distributed optimization with uncertainties for multiagent systems. We propose a new distributed consensus scenario approach, handling uncertainties through a scenario program method. An approximate solution is developed, followed by a distributed estimation algorithm to manage large data volumes without a centralized approach. Our design inherently offers robustness against adversarial attacks and preserves data privacy. We provide rigorous convergence analysis and demonstrate the effectiveness of our approach through application examples in regression and robust internal model control. This work presents a significant step towards holistic solutions for optimization in safety-critical multiagent systems.

关键词： Uncertainty Optimization Cost function Multi-agent systems Measurement uncertainty Linear programming Noise Load modeling Eigenvalues and eigenfunctions Dynamical systems Optimization with uncertainties distributed algorithms scenario approach consensus algorithm multiagent distributed learning

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Secure Task Offloading in Blockchain-Enabled MEC Networks With Improved PBFT consensus

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2025年第2期11卷 1225-1243页

作者： Du, Jianbo Yu, Zuting Sun, Aijing Jiang, Jing Zhao, Haitao Zhang, Ning Wu, Celimuge Yu, F. Richard Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian 710121 Peoples R China Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing 210003 Peoples R China Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Univ Electrocommun Meta Networking Res Ctr Tokyo 1828585 Japan Carleton Univ Syst & Comp Engn Ottawa ON K1S 5B6 Canada

In this paper, we investigate the secure task offloading and computation resource allocation issues in a consortium blockchain-enabled multi-access edge computing (MEC) system. Specifically, edge servers and a cloud center provides user equipments (UEs) with augmented computing power for task processing, while consortium blockchain can provide trust and secure guarantee to UEs in task offloading. Within the MEC system, we intend to minimize the task processing cost of all UEs by jointly optimizing the binary task offloading decision and the computation resource block allocation. Meanwhile, in the blockchain system, we first enhance the consensus procedure by proposing an improved practical Byzantine fault tolerance (IPBFT) consensus algorithm, and then conduct consensus committee selection, thus to minimize consensus delay and fail ratio. The two systems are jointly optimized, subjecting to the computation power of edge nodes, the node number limitation of IPBFT, the task processing and blockchain consensus delay, etc. To address the problem effectively, we reform it into a Markov decision process (MDP) and use proximal policy optimization (PPO) to dynamically learn the optimal joint solution. Simulation results demonstrate that our proposed algorithm converges fast, and performs well in total reward maximization, and UEs' cost, consensus delay and fail ratio minimization.

关键词： Blockchains Resource management Servers Optimization Delays consensus algorithm Heuristic algorithms Computation offloading deep reinforcement learning proximal policy optimization (PPO) blockchain improved practical Byzantine fault tolerance (IPBFT)

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On Distributed Average consensus algorithms

arXiv

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arXiv 2025年

作者： Merched, Ricardo Dept.of Electronics and Computer Engineering Universidade Federal do Rio de Janeiro Brazil

Average consensus (AC) strategies play a key role in every system that employs cooperation by means of distributed computations. To promote consensus, an N-agent network can repeatedly combine certain node estimates until their mean value is reached. Such algorithms are typically formulated as (global) recursive matrix-vector products of size N, where consensus is attained either asymptotically or in finite time. We revisit some existing approaches in these directions and propose new iterative and exact solutions to the problem. Considering directed graphs, this is carried out first by interplaying with standalone conterparts, while underpinned by the so-called eigenstep method of finite-time convergence. Second, we compute the solution via an exact algorithm that requires, overall, as little as OpNq additions. For undirected graphs, the latter compares favorably to existing schemes that require, in total, OpKN2q multiplications to deliver the AC, where K refers to the number of distinct eivenvalues of the underlying graph Laplacian matrix. Copyright © 2025, The Authors. All rights reserved.

关键词： consensus algorithm

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Blockchain-Enabled Trust Management in Internet of Vehicles: A Joint Pre-Reward-Penalty and consensus Approach

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IEEE INTERNET OF THINGS JOURNAL 2025年第6期12卷 6961-6978页

作者： Chen, Chen Wang, Lankai Shi, Quan Nantong Univ Sch Informat Sci & Technol Nantong 226019 Peoples R China Nantong Univ Sch Transportat & Civil Engn Nantong 226019 Peoples R China

The Internet of Vehicles (IoV) is a transformative technology extensively employed in modern intelligent transportation systems. However, managing trust within the IoV presents significant challenges owing to its decentralized architecture, inclusivity, and widespread network. This article proposes a novel trust management scheme for IoV that integrates blockchain technology with a pre-reward-penalty incentive mechanism and trust-based consensus algorithm to address the existing issues of security, scalability, and transparency. The proposed scheme establishes a decentralized trust management system that assesses the reliability of vehicle nodes using a combination of initial trust, local trust, and global trust metrics. Furthermore, it introduces an innovative pre-reward-penalty mechanism that leverages convolutional neural networks (CNNs) to predict message authenticity, thereby promoting truthful participation and information sharing among nodes and enhancing the system's overall credibility. The trust-based consensus algorithm, supported by the pre-reward-penalty incentive mechanism, ensures data consistency and reliability, thereby improving security and robustness. The experimental results demonstrate significant improvements in security, scalability, and efficiency compared to conventional trust management approaches. These findings offer a pioneering solution for trust management in IoV, with substantial theoretical implications and practical applications.

关键词： Blockchains Trust management Security consensus protocol Reliability Vehicle dynamics consensus algorithm Bayes methods Scalability Transportation Blockchain consensus algorithm convolutional neural networks (CNNs) Internet of Vehicles (IoV)

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DynaNet: A dynamic BFT consensus framework

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JOURNAL OF SYSTEMS ARCHITECTURE 2025年 162卷

作者： Li, Jiarui Zhang, Guoyan Liu, Duan Zhou, Fei Li, Leibo Meng, Weizhi Shandong Univ Qingdao Shandong Peoples R China Shandong Inst Blockchain Jinan Shandong Peoples R China Tech Univ Denmark Lyngby Denmark

In a blockchain system, allowing nodes to change during runtime through consensus protocols is an effective way to enhance the scalability and security of the blockchain. However, some limitations of the traditional membership change methods prevent them from meeting the continuously expanding scale of blockchain networks. The paper proposes a membership change framework based on byzantine fault tolerance (BFT) consensus: DynaNet. Compared to similar membership change methods, DynaNet can make any number of members join and leave the system with just one consensus round and offer tremendous flexibility: it can be integrated with most synchronous BFT consensus protocols, endowing it with membership change capabilities. We showcase its integration with HotStuff: D-HotStuff and prove its safety and liveness. The experiment shows that D-HotStuff performs well in latency and throughput, and its multi-node change mode is more practical.

关键词： consensus algorithm Membership change Dynamic BFT Partially synchronous model

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X-RAFT: Improve RAFT consensus to Make Blockchain Better Secure EdgeAI-Human-IoT Data

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2025年第1期13卷 22-33页

作者： Li, Fengqi Wang, Jiaheng Xie, Weilin Tong, Ning Wang, Deguang Dalian Jiaotong Univ Sch software Dalian 116028 Peoples R China Dalian Univ Technol Sch software Dalian 116024 Peoples R China

The proliferation of IoT devices, advancements in edge computing, and innovations in AI technology have created an ideal environment for the birth and growth of Edge AI. With the trend towards the Internet of Everything (IoE), the EdgeAI- Human-IoT architectural framework highlights the necessity for efficient data exchange interconnectivity. Ensuring secure data sharing and efficient data storage are pivotal challenges in achieving seamless data interconnection. Owing to its simplicity, ease of deployment, and consensus-reaching capabilities, the RAFT consensus algorithm, which is commonly used in distributed storage, faces limitations as the IoT scale expands. The computational, communication, and storage capabilities of nodes are constraints, and the security of data remains a concern. To address these complex challenges, we introduce the X-RAFT consensus algorithm, which is tailored for blockchain technology. This algorithm enhances system performance and robustness, mitigates the impact of system load, enhances system sustainability, and increases Byzantine fault tolerance. Through analysis and simulations, our proposed solution has been evidenced to provide reliable security and efficient performance.

关键词： Blockchains Internet of Things Voting Servers Fault tolerant systems Fault tolerance consensus algorithm Computer crashes Throughput Sharding Blockchain EdgeAI- human -IoT internet of things (IoT) RAFT

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