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A Hybrid consensus algorithm for Collaborative Protection of Multi-domain Education Data

JOURNAL OF INTERNET TECHNOLOGY 2024年第7期25卷 963-975页

作者： Wu, Xianglin Meng, Tianhao Huang, Haotian Liu, Lianhai Zhang, Jingwei Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin Peoples R China Hezhou Univ Sch Artificial Intelligence Hezhou Peoples R China

Sharing education data among universities can inspire many new applications and developments. At the same time, blockchain technology can ensure the security and sharing of education data. However, the consensus algorithm cannot meet the requirements of low latency and high throughput in the current education blockchain. Therefore, we propose a hybrid consensus algorithm based on a master- slave blockchain (MSB) for multi-domain education data management (EDM) to maintain data consistency. First, we design a double-layer architecture of the MSB that can efficiently and securely handle large-scale education data from universities. Second, facing low consensus efficiency for EDM, we propose the hybrid consensus algorithm that combines the reputation-based RAFT (R-RAFT) and the multi-party optimized PBFT (M-PBFT). The experiment proves that the proposed solution can obviously improve the throughput compared with the single chain. Furthermore, it also performs well on latency, consensus speed, and Byzantine fault tolerance.

关键词： Education data management Master-slave blockchain consensus algorithm

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A Discrete-Time Reputation-Based Resilient consensus algorithm for Synchronous or Asynchronous Communications

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2024年第1期69卷 543-550页

作者： Ramos, Guilherme Silvestre, Daniel Silvestre, Carlos Univ Lisbon Dept Informat Inst Super Tecn P-1649004 Lisbon Portugal Inst Telecomunicacoes P-1049001 Lisbon Portugal Univ Lisbon NOVA P-1649004 Lisbon Portugal Univ Lisbon Inst Syst & Robot Inst Super Tecn P-1049001 Lisbon Portugal Univ Macau Fac Sci & Technol Dept Elect & Comp Engn Macau 999078 Peoples R China Univ Lisbon Inst Super Tecn Lisbon Portugal

We tackle the problem of a set of agents achieving resilient consensus in the presence of attacked agents. We present a discrete-time reputation-based consensus algorithm for synchronous and asynchronous networks by developing a local strategy where, at each time, each agent assigns a reputation (between zero and one) to each neighbor. The reputation is then used to weigh the neighbors' values in the update of its state. Under mild assumptions, we show that: 1) the proposed method converges exponentially to the consensus of the regular agents;2) if a regular agent identifies a neighbor as an attacked node, then it is indeed an attacked node;3) if the consensus value of the normal nodes differs from that of any of the attacked nodes' values, then the reputation that a regular agent assigns to the attacked neighbors goes to zero. Further, we extend our method to achieve resilience in scenarios where there are noisy nodes, dynamic networks, and stochastic node selection. Finally, we illustrate our algorithm with several examples, delineating some attacks that can be dealt with by the current proposal but not by the state-of-the-art approaches.

关键词： consensus algorithm Heuristic algorithms Fault tolerant systems Fault tolerance Computational complexity Steady-state Network topology Agents and autonomous systems computer networks fault tolerant systems reputation systems

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Light-PerIChain: Using lightweight scalable blockchain based on node performance and improved consensus algorithm in IoT systems

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COMPUTER COMMUNICATIONS 2024年 213卷 246-259页

作者： Fathi, Fateme Baghani, Mina Bayat, Majid Imam Khomeini Int Univ Dept Tech Engn Qazvin Iran Shahed Univ Dept Comp Engn Tehran Iran

With the development of the industry and the increase of smart devices in recent years, the Internet of Things has expanded as one of the solutions to meet human needs in smart societies. However, this emerging technology suffers from security vulnerabilities. In recent years, blockchain has attracted much attention due to its decentralization. However, blockchain is computationally expensive, with limited scalability and high overhead costs. Also, designing a secure and robust blockchain for use in the Internet of Things is challenging. In this article, we provide solutions to improve the sharding method to achieve a lightweight and scalable blockchain and enhance the efficiency of the Internet of Things. To assign nodes to shards in the first round, we use the Verifiable Random Function (VRF), and after a few rounds, nodes are assigned to shards according to their point and performance in the network. We use the IBFT consensus algorithm to process the transaction in shards. Unlike other consensus algorithms based on Byzantine fault tolerance, this algorithm requires 2f+ 1 replicas instead of 3f +1 for fault tolerance. Also, in this method, the team leader's shard is considered, so nodes with the highest performance assign to this shard. If the malicious behavior of the team leader is detected, one of the nodes in the team leader's shard is replaced by it. For cross-transaction processing, we present an improved two-phase commit method that solves many problems with existing two-phase commit methods. Finally, we analyze our design for efficiency and security. Our qualitative arguments show that this design is resistant to several security attacks and that the scalability and throughput of IoT are increased compared to previous designs.

关键词： Internet of Things Blockchain Sharding Lightweight scalable blockchain Performance consensus algorithm Cross-shard transaction

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A Distributed Proximal consensus algorithm for Energy Saving in Ethylene Production

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年第3期35卷 3052-3061页

作者： Nie, Rong Du, Wenli Wang, Ting Li, Zhongmei He, Shuping East China Univ Sci & Technol Minist Educ Key Lab Smart Mfg Energy Chem Proc Shanghai 200237 Peoples R China Qingyuan Innovat Lab Quanzhou 362801 Peoples R China Anhui Univ Sch Elect Engn & Automat Minist Educ Key Lab Intelligent Comp & Signal Processing Hefei 230601 Peoples R China Chengdu Univ Sch Elect Informat & Elect Engn Chengdu 610106 Peoples R China

This article presents a distributed optimization framework in order to solve the plant-wide energy-saving problem of an ethylene plant. First, the ethylene production process is abstracted into a distributed network, and then, a new distributed consensus algorithm is proposed, which is called adaptive step-size-based distributed proximal consensus algorithm (ASS-DPCA). This algorithm can dynamically adjust the step size and automatically abandon the irrational evolutionary route while eliminating the dependence of optimization algorithms on model gradient information. Moreover, the designed algorithm is able to converge to an optimal solution for any convex cost functions and approach to a convex constraint set of agents over an undirected connected graph. Finally, the results of numerical simulation and industrial experiments show that the algorithm can reduce the total energy consumption of an ethylene plant with less computing time and assured consensus.

关键词： Production Optimization Energy consumption consensus algorithm Upper bound Petrochemicals Linear programming Distributed optimization energy saving ethylene plant-wide optimization proximal consensus algorithm

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ReCaLS-in-DLT: resilient consensus algorithm for leader selection in distributed ledger technology

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2025年第5期28卷 1-17页

作者： Hussain, Munir Mehmood, Amjad Khan, Muhammad Altaf Wang, Huihui Song, Houbing Herbert Maple, Carsten Kohat Univ Sci & Technol Inst Comp Kohat Pakistan Univ Warwick Secure Cyber Syst Res Grp CSCRG WMG Coventry CV4 7AL England Northeastern Univ Comp Programs 130017th St N 1500 Arlington VA 22209 USA Univ Maryland Dept Informat Syst Baltimore MD USA

Distributed ledger technology (DLT) is most widely used in many areas for example healthcare, finance, public welfare, and Internet of Things (IoT) to provide security and effi- ciency. The consensus algorithm is a key component of DLT-based networks that plays a vital role in maintaining the performance of the network and ensuring security. We proposed a consensus algorithm that selects a leader or miner node based on a lucky number for block mining. The proposed algorithm is not only scalable but also enhances security during the consensus process in the presence of less trustworthy nodes, the selected miner node is re-authenticated by the trusted authority before adding a block in the ledger. Apart from the re-authentication process, the trust level of the miner node is also checked. Statistical analysis is performed to prove the security of the proposed algorithm. The results demonstrate that our proposed algorithm offers a good level of resistance against abnormal behavior of the network nodes. Furthermore, performance evaluation is also performed through the Hyper-ledger Fabric Blockchain platform. The simulation results show that the proposed consensus algorithm provides high throughput, low latency, low CPU utilization, and communication bandwidth consumption as compared to the state- of-the-art benchmark proposed in the literature. The lightweight and secure nature of the proposed algorithm makes it a suitable solution for the consensus process in DLT.

关键词： Hyperledger fabric DLT consensus algorithm Vote-based Proof-based Trust

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Differential Evolution-Based Sample consensus algorithm for the Matching of Remote Sensing Optical Images With Affine Geometric Differences

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IEEE ACCESS 2024年 12卷 54481-54492页

作者： Paul, Sourabh Tiwari, Ravi Rahul, Amit Kumar Singh, Manoj Kumar Gupta, Pratham Vellore Inst Technol VIT Sch Elect Engn SENSE Chennai 600127 Tamil Nadu India Vellore Inst Technol VIT Sch Adv Sci SAS Div Math Chennai 600127 Tamil Nadu India Vellore Inst Technol VIT Sch Comp Sci & Engn SCOPE Chennai 600127 Tamil Nadu India

Optical image matching has been a recent trend in the field of remote sensing image processing. It is considered as a challenging problem due to the existence of significant geometric variations as well as intensity differences between the images. Scale invariant feature transform (SIFT) is one of the most effective schemes to handle these factors. However, it produces many false matches in the matching of the remote sensing images which effect its performance. In order to address this issue, a novel Differential Evolution-based Sample consensus algorithm (DESCA) is proposed to eliminate these false matches and retain the correct matches. The proposed DESCA scheme is very effective for the images having significant affine geometric differences. It has the ability to provide more correct matches. Several sets of remote sensing optical image pairs are used to test the performance of the proposed method. It obtains the Root Mean Square Error (RMSE) value in the range of 0.67 to 0.95 pixels which indicates that the sub-pixel accuracy is achieved. The experimental results show that the proposed method provides more correct matching pairs and better mutual information (MI) values than the state-of-the-art methods.

关键词： Feature extraction Vectors Optical sensors Optical imaging Adaptive optics Optimization Image matching consensus algorithm Scale-invariant feature transform (SIFT) differential evolution (DE) sample consensus algorithm (SCA)

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Q-Learning Improved Lightweight consensus algorithm for Blockchain-Structured Internet of Things

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IEEE INTERNET OF THINGS JOURNAL 2024年第2期11卷 2855-2869页

作者： Li, Wenjuan Zhang, Qifei Deng, Shuiguang Zhou, Bin Wang, Ben Cao, Jian Hangzhou Normal Univ Sch Informat Sci & Technol Hangzhou 310018 Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou 311051 Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310027 Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Technol Shanghai 200240 Peoples R China

Security and trust have become the key issues in the Internet of Things (IoT) environment. Characterized by the centralized control and high-energy consumption, the traditional trust management schemes are not suitable for the IoT systems, in which most of the interactions are short-duration, random and maybe one-time, and the terminal devices always have resource constraints. Therefore, this article proposes a distributed and two-layered trust management framework based on blockchain architecture for IoT. The hierarchical architecture of the cloud, the edge, the IoT subgroups, and devices solves the resource limitation problem and improves the privacy protection of the IoT applications. And a novel lightweight Q-learning improved DPoS consensus algorithm named QV-DPoS is proposed to solve the problems of large energy consumption and high complexity of consensus mechanism of blockchain. Ethereum is used to build a blockchain-based IoT prototype system, and some experiments were designed to verify whether the proposed platform can successfully conduct trust management and achieve identity and behavior authentication between the IoT entities. Moreover, the simulation experiments based on NetLogo is also designed to test the performance of the trust and consensus mechanisms. The results of the experiments show that the proposed mechanisms can effectively enhance the credibility of the interactions in the IoT environments, improve the transaction success rate, and reduce energy consumption at least 10% compared with the traditional algorithms.

关键词： Blockchain consensus algorithm low-energy consumption Q-learning trust management in Internet of Things (IoT)

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Long-Term Proof-of-Contribution: An Incentivized consensus algorithm for Blockchain-Enabled Federated Learning

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2024年第5期17卷 2558-2570页

作者： Zhao, Yao Qu, Youyang Xiang, Yong Chen, Feifei Gao, Longxiang Deakin Univ Sch Informat Technol Burwood Vic 3125 Australia Qilu Univ Technol Shandong Acad Sci Shandong Comp Sci Ctr Key Lab Comp Power Network & Informat SecurMinist Jinan 250316 Peoples R China Shandong Fundamental Res Ctr Comp Sci Shandong Prov Key Lab Comp Networks Jinan 250316 Peoples R China

The surge in data collected by local devices has given rise to a distributed machine learning architecture named Federated Learning (FL) for privacy-preserving model training. However, the security of centralized aggregation of local models becomes a primary concern, which can be mitigated by Blockchain-enabled Federated Learning (BFL) to facilitate decentralized model aggregation. In BFL, consensus and incentive are two of the key components that impact the scalability, security, and consistency of the system. Existing joint solutions focus on selecting a block producer based on client contributions to model training but overlook contributions to blockchain consensus and lack consideration for correlations across communication rounds, inevitably affecting incentive performance. Motivated by these, we make the first attempt to achieve blockchain consensus with a long-term incentive guarantee for BFL systems. Following a generalizable BFL workflow, we decouple the global contribution of BFL clients into four rigorously modeled metrics, and formulate the block producer selection problem as a long-term total contribution maximization problem with reward constraints. A Long-term Proof-of-Contribution algorithm named LPoC is developed to handle this problem efficiently. In each communication round, LPoC identifies an optimal block producer that can maximize total contributions from a long-term perspective while allocating rewards to continuously motivate clients to contribute to BFL. We provide a detailed analysis of time complexity and performance bounds, followed by extensive experimental evaluations. The results demonstrate the effectiveness of LPoC in maximizing long-term total contribution, improving consensus efficiency, and upgrading training performance.

关键词： Blockchain-enabled federated learning consensus algorithm incentive mechanism long-term Blockchain-enabled federated learning consensus algorithm incentive mechanism long-term

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Hybrid Raft-PoW Blockchain consensus algorithm

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IEEE ACCESS 2025年 13卷 72067-72076页

作者： Ulukok, Mehtap Kose Sariyildiz, Irfan Evrim, Vesile Cyprus Aydin Univ Dept Software Engn TR-99010 Mersin Northern Cyprus Turkiye European Univ Lefke Dept Comp Engn TR-99010 Mersin Northern Cyprus Turkiye

The Raft consensus algorithm is widely used in private networks as an alternative to the energy-intensive PoW consensus algorithm in blockchains. The Raft consensus algorithm's voting mechanism performs well in reliable and well-planned networks with optimized timeouts. However, in unreliable or poorly configured networks, it encounters several challenges. These include multiple candidacies, repeated election cycles, insufficient or failed leader elections during network splits, prolonged leader election times and vulnerability to Sybil attacks. In this study, a novel Hybrid Raft-PoW consensus algorithm is introduced. It integrates the hash puzzle-based competition of the PoW consensus algorithm with the fast leader election mechanism of the Raft consensus algorithm. This combination ensures both speed and certainty in leader election, ensuring that leadership is delegated to the most capable nodes. At the same time, it promotes decentralization by ensuring a fair distribution across nodes, achieving at least 80% leadership distribution. Therefore, the proposed Hybrid Raft-PoW consensus algorithm improves or eliminates problems caused by Raft consensus algorithm's leader election mechanism.

关键词： Voting consensus algorithm Blockchains Security Leadership Partitioning algorithms Energy consumption Internet of Things Clustering algorithms Simulation Blockchain technology consensus algorithms proof of work raft

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Performance enhancement in blockchain based IoT data sharing using lightweight consensus algorithm

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SCIENTIFIC REPORTS 2024年第1期14卷 1-13页

作者： Haque, Ehtisham Ul Abbasi, Waseem Almogren, Ahmad Choi, Jaeyoung Altameem, Ayman Rehman, Ateeq Ur Hamam, Habib COMSATS Univ Islamabad Dept Comp Sci Abbottabad Campus Islamabad 22200 Pakistan Univ Lahore Dept Comp Sci Sargodha Campus Lahore 40100 Pakistan King Saud Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh 11633 Saudi Arabia Gachon Univ Sch Comp Seongnam 13120 South Korea King Saud Univ Coll Appl Studies & Community Serv Dept Nat & Engn Sci Riyadh 11543 Saudi Arabia Univ Moncton Fac Engn Moncton NB E1A3E9 Canada Univ Johannesburg Sch Elect Engn ZA-2006 Johannesburg South Africa Hodmas Univ Coll Taleh Area Mogadishu 521376 Banadir Somalia Spectrum Bridges Acad Excellence Tunis 1002 Centre Ville Tunisia

The proliferation of Internet of Things (IoT) devices generates vast amounts of data, traditionally stored, processed, and analyzed using centralized systems, making them susceptible to attacks. Blockchain offers a solution by storing and securing IoT data in a distributed manner. However, the low performance and poor scalability of blockchain technology pose significant challenges for its application in IoT networks. The primary obstacle is the distributed consensus protocol, while ensuring data transparency, integrity, and immutability in a decentralized and untrusted circumstances which often compromises scalability. To address this issue, this paper introduces the use of the Delegated Proof of Stake (DPoS) consensus algorithm and sharding techniques to enhance scalability in blockchain-based IoT networks. Experimental results indicate that system throughput increases synchronously with the test load. Our findings reveal a tradeoff between throughput, latency, and up-downstream time on the Inter Planetary File System (IPFS). Given the critical importance of latency and throughput in IoT networks, the results demonstrate that DPoS offers high throughput, parallel processing, and robust security while efficiently scaling the network. Furthermore, at a test load of 500 Transactions Per Second (TPS), the system achieves a maximum throughput of approximately 11.094 ms. However, when the test load exceeds 2000 TPS, the total processing time for transactions extends to 11.205 ms. This method is particularly suitable for constrained IoT networks. Compared to previous edge computing-based approaches, our scheme demonstrates superior throughput performance.

关键词： Blockchain consensus algorithm Data storage Internet of things Parallel execution Scalability Sharding Smart contract

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