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A secure and highly efficient blockchain PBFT consensus algorithm for microgrid power trading

SCIENTIFIC REPORTS 2024年第1期14卷 1-17页

作者： Yao, Zhongyuan Fang, Yonghao Pan, Heng Wang, Xiangyang Si, Xueming Zhongyuan Univ Technol Frontier Informat Technol Res Inst Zhengzhou 450007 Peoples R China Henan Int Joint Lab Blockchain & Data Sharing Zhengzhou 450007 Peoples R China

There are a series of challenges in microgrid transactions, and blockchain technology holds the promise of addressing these challenges. However, with the increasing number of users in microgrid transactions, existing blockchain systems may struggle to meet the growing demands for transactions. Therefore, this paper proposes an efficient and secure blockchain consensus algorithm designed to meet the demands of large-scale microgrid electricity transactions. The algorithm begins by utilizing a Spectral clustering algorithm to partition the blockchain network into different lower-level consensus set based on the transaction characteristics of nodes. Subsequently, a dual-layer consensus process is employed to enhance the efficiency of consensus. Additionally, we have designed a secure consensus set leader election strategy to promptly identify leaders with excellent performance. Finally, we have introduced an authentication method that combines zero-knowledge proofs and key sharing to further mitigate the risk of malicious nodes participating in the consensus. Theoretical analysis indicates that our proposed consensus algorithm, incorporating multiple layers of security measures, effectively withstands blockchain attacks such as denial of service. Simulation experiment results demonstrate that our algorithm outperforms similar blockchain algorithms significantly in terms of communication overhead, consensus latency, and throughput.

关键词： Blockchain Distributed energy trading consensus algorithm Spectral clustering Zero-knowledge proof

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A Study of Privacy Preservation in Average consensus algorithm via Deterministic Obfuscation Signals

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2024年第1期11卷 534-546页

作者： Rezazadeh, Navid Kia, Solmaz S. Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA 92697 USA

This article is a study on the use of additive obfuscation signals to keep the reference values of the agents in the continuous-time Laplacian average consensus algorithm private from eavesdroppers. Obfuscation signals are perturbations that agents add to their local dynamics and their transmitted-out messages to conceal their private reference values. An eavesdropper is an agent inside or outside the network that has access to some subset of the interagent communication messages, and its knowledge set also includes the network topology. Rather than focusing on using a zero-sum and vanishing additive signal, our work determines the necessary and sufficient conditions that define the set of admissible obfuscation signals that do not perturb the convergence point of the algorithm from the average of the reference values of the agents. Of theoretical interest, our results show that this class includes nonvanishing signals as well. Given this broader class of admissible obfuscation signals, we define a deterministic notion of privacy preservation. In this definition, privacy preservation for an agent means that neither the private reference value nor a finite set of values to which the private reference value of the agent belongs to can be obtained. Then, we evaluate the agents' privacy against eavesdroppers with different knowledge sets.

关键词： Privacy Laplace equations Additives Convergence Perturbation methods Heuristic algorithms Sufficient conditions consensus algorithm network systems privacy preservation

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Context-Aware consensus algorithm for Blockchain-Empowered Federated Learning

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2024年第2期12卷 491-503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 CtrMinist EducKey Lab Comp Pow Shandong Fundamental Res Ctr Comp SciShandong Pro Jinan 250316 Peoples R China

Supported by cloud computing, Federated Learning (FL) has experienced rapid advancement, as a promising technique to motivate clients to collaboratively train models without sharing local data. To improve the security and fairness of FL implementation, numerous Blockchain-empowered Federated Learning (BFL) frameworks have emerged accordingly. Among them, consensus algorithms play a pivotal role in determining the scalability, security, and consistency of BFL systems. Existing consensus solutions to block producer selection and reward allocation either focus on well-resourced scenarios or accommodate BFL based on clients' contributions to model training. However, these approaches limit consensus efficiency and undermine reward fairness, due to involving intricate consensus processes, disregarding clients' contributions during blockchain consensus, and failing to address lazy client problems (malicious clients plagiarizing local model updates from others to reap rewards). Given the aforementioned challenges, we make the first attempt to design a joint solution for efficient consensus and fair reward allocation in heterogeneous BFL systems with lazy clients. Specifically, we introduce a generalizable BFL workflow that can address lazy client problems well. Based on it, the global contribution of BFL clients is decoupled into five dominant metrics, and the block producer selection problem is formulated as a reward-constraint contribution maximization problem. By addressing this problem, the optimal block producer that maximizes global contribution can be identified to orchestrate consensus processes, and rewards are distributed to clients in proportion to their respective global contributions. To achieve it, we develop a Context-aware Proof-of-Contribution consensus algorithm named CPoC to reach consensus and incentive simultaneously, followed by theoretical analysis of lazy client problems and privacy issues. Empirical results on widely-used datasets demonstrate the ef

关键词： Training Blockchains Delays Computational modeling consensus algorithm Federated learning Cloud computing blockchain federated learning lazy client incentive mechanism

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Optimising islanded AC microgrid control: A hierarchical approach with FCS-VMPC and consensus algorithm

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RESULTS IN ENGINEERING 2025年 25卷

作者： Khan, Zawar Aamir, Muhammad Khan, Rizwanullah Yousof, Mohd Fairouz Mohd Pak Austria Fachhhsch Inst Appl Sci & Technol Mang Pakistan Univ Tun Hussein Onn Malaysia Fac Elect & Elect Engn Batu Pahat Johor Malaysia

The growing integration of distributed generation (DG) from renewable energy sources (RES) in modern power systems highlights the need for advanced hierarchical control strategies. The primary layer is typically implemented using a linear controller, while the secondary control relies on complex control strategies. Due to this hierarchical control AC microgrid (MG) faces unequal power sharing or power quality problems. This paper presents a hierarchical control scheme for islanded AC MG to effectively manage power between DG units. The scheme operates with a non-linear controller consisting of finite control set-voltage model predictive control (FCS-VMPC) at the primary layer and a consensus algorithm at the secondary layer. Primary control, utilizing droop control and FCS-VMPC, is independently implemented for frequency and voltage regulation across DG units. Droop control manages power distribution between DG units and loads. Meanwhile, the secondary layer based on the consensus algorithm collaborates with FCS-VMPC to establish reference voltage values and adjust deviations at the primary level. The proposed hierarchical control facilitates communication between adjacent nodes by a sparse network. This reduces the complexity of the network with FCS-VMPC at the primary and consensus algorithm at the secondary layer. The secondary controller's effectiveness is tested against transients, unbalanced loads, and dynamic load changes. The results confirm that the MG effectively supplies power while maintaining stable voltage and frequency, achieving a total harmonic distortion (THD) of 0.95 % and a maximum voltage deviation of 0.0001 pu respectively.

关键词： consensus algorithm Distributed generation units Droop control Model predictive control

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Efficient consensus algorithm based on improved DPoS in UAV-assisted mobile edge computing

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COMPUTER COMMUNICATIONS 2023年第1期207卷 86-99页

作者： Song, Mingyang Li, Chunlin Ye, Jingsong Gong, Xunqiang Luo, Youlong Wuhan Univ Technol Dept Comp Sci Wuhan 430063 Peoples R China East China Univ Technol Minist Nat Resources Key Lab Mine Environm Monitoring & Improving Poyan Nanchang 330013 Peoples R China China Acad Transportat Sci Beijing 100029 Peoples R China Sichuan Tourism Coll Chengdu 610100 Peoples R China Hebei Normal Univ Sci & Technol Marine Econ & Coastal Econ Belt Res Ctr Qinhuangdao 066004 Peoples R China Wuyi Univ Fujian Key Lab Big Data Applicat & Intellectualiza Nanping 354300 Fujian Peoples R China

Aiming at the problems of low decentralization, low motivation for node voting, and malicious behavior of nodes for the traditional DPoS consensus mechanism in the blockchain-based UAV-assisted mobile edge computing environment, this paper proposes an improved DPoS-based consensus mechanism approach. First, the framework of a blockchain-based UAV-assisted mobile edge computing system is given, and the consensus mechanism design problem in this framework is analyzed. Second, a proxy node selection model is established based on the rights and votes obtained by the blockchain nodes, and the proxy nodes are selected to participate in the consensus process of the current cycle. Then, the voting behavior, block generation behavior, and block verification behavior of nodes are classified into positive and malicious behaviors to reward and punish the reputation value of nodes. Finally, a blockchain-based UAV-assisted mobile edge computing experimental environment is built, and the TDPoS algorithm, ADRP algorithm, and RDPoS algorithm are used as benchmark algorithms to experimentally compare with the proposed improved DPoS consensus-based algorithm. The experimental results show that the algorithms in this paper can improve network throughput, reduce block-out delay, and increase the proportion of secure proxy nodes.

关键词： consensus algorithm DPoS UAV-assisted mobile edge computing

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Optimisation method of IoT financial data transmission efficiency based on consensus algorithm of blockchain technology

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2024年第3-4期15卷 295-305页

作者： Yang, Xiaojie Shijiazhuang Coll Appl Technol Dept Econ & Trade Shijiazhuang Hebei Peoples R China

The financial industry faces the challenge of slow data transmission efficiency and poor security. To address these issues, a new IoT financial data transmission model based on the blockchain DPoS consensus algorithm has been designed. This model introduces reputation and network nodes to enhance system stability. By evaluating and selecting reliable nodes as consensus validators, the negative impact of malicious nodes can be mitigated. Gateway nodes can act as intermediate nodes to minimise transmission delay and network congestion, while improving transmission speed and reliability. The performance test results showed that the honest nodes of the research algorithm were stable at about 91% in the 6th round of voting, while 998 valid blocks were produced at the end of 10 rounds of voting. In practical application tests, the lowest transmission rates were 2286 bps and 536 bps for different financial data sets, and the highest packet loss rates were 0.12% and 1.24%, respectively. Taken together, the above data illustrates that the research model is extremely secure and stable, and has high-data transmission efficiency and low packet loss. The research results and conclusions can provide more practical, secure and efficient solutions for data transmission problems in related fields.

关键词： internet of things consensus algorithm data transfer finance blockchain

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consensus algorithm-Based Distributed Generator Sharing for Isolated Heterogeneous Microgrids 8

Consensus Algorithm-Based Distributed Generator Sharing for ...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Silva, Paulo Fernando Rodrigues, Diego T. Filho, José De Arimatéia Olimpio De Oro Arenas, Luis Bonaldo, Jakson Paulo Paredes, Helmo Kelis Morales Sorocaba Brazil Departament of Eletrical Engineering Cuiabá Brazil

ISBN: (纸本)9798350321128

The expanding use of Renewable Energy Sources (RES) has introduced a new concept of microgrids, suggested in this work as heterogeneous microgrids (HMGs). HMGs comprise single-phase and three-phase RES-based distributed generators (DGs) operating together within the same microgrid to supply linear and nonlinear loads. The connection of single-phase loads, especially nonlinear ones, leads to imbalances and harmonic distortions in currents and, consequently, in asymmetric and distorted voltages. This paper presents a novel secondary control method based on consensus algorithms and symmetrical components to achieve phase-power sharing among DGs in HMGs. The symmetrical components enable the implementation of virtual impedance loops, allowing independent control of the negative and zero sequence components provided by the DGs, regardless of their topology (single-phase or three-phase). Moreover, the consensus algorithm establishes an agreement regarding voltage and frequency regulation among the DGs operating in the HMG, thereby promoting equal power sharing among the DGs phases. Finally, the proposed methodology effectiveness is validated by the simulation results. © 2023 IEEE.

关键词： consensus algorithm distributed control microgrids (MGs) Multifunctional inverters power quality

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Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on consensus algorithm Considering Lossy Communication Network and Uncertainty

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 352-364页

作者： Abdelfattah A.Eladl Magda I.El-Afifi Magdi M.El-Saadawi Bishoy E.Sedhom Electrical Engineering Department Faculty of EngineeringMansoura UniversityEl-MansouraEgypt

This paper proposes an IoT-Fog-Cloud distributed consensus algorithm for solving the energy hub(EH)dispatch problem with packet-dropping communication links and some of EH elements'*** generating and consumption unit in this algorithm is required to estimate total power generated,total load,and power *** node coordination is accomplished using a distributed *** a distributed approach wins in work sharing,enduring a single link failure,effective decision-making,quickest convergence,and autonomy for global power *** method works with all grid types in connected and islanded *** total operation cost and emissions while meeting total demand and system constraints are the most crucial contributions of this *** case studies are applied to explain performance and effectiveness of the proposed algorithm with different packet loss *** uncertainty,sensitivity of the system was *** show mismatch between generated and consumed power is improved by 100%in the electricity grid,99.94%in heating grid,and 99.91%in gas ***,total operating cost,total emissions,and emissions cost decreased by 8.6%,13.48%,and 18.73%,respectively.

关键词： consensus algorithm CO_(2)emissions energy hubs multi-energy systems packet drops

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Blockchain Assisted Data Edge Verification With consensus algorithm for Machine Learning Assisted IoT

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IEEE ACCESS 2023年 11卷 55370-55379页

作者： Vaiyapuri, Thavavel Shankar, K. Rajendran, Surendran Kumar, Sachin Acharya, Srijana Kim, Hyunil Prince Sattam bin Abdulaziz Univ Coll Comp Engn & Sci Al Kharj 11942 Saudi Arabia Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Comp Sci & Engn Chennai 602105 India South Ural State Univ Big Data & Machine Learning Lab Chelyabinsk 454080 Russia Kongju Natl Univ Dept Convergence Sci Gongju Si 32588 Chungcheongnam South Korea

Internet of Things (IoT) devices are becoming increasingly ubiquitous in daily life. They are utilized in various sectors like healthcare, manufacturing, and transportation. The main challenges related to IoT devices are the potential for faults to occur and their reliability. In classical IoT fault detection, the client device must upload raw information to the central server for the training model, which can reveal sensitive business information. Blockchain (BC) technology and a fault detection algorithm are applied to overcome these challenges. Generally, the fusion of BC technology and fault detection algorithms can give a secure and more reliable IoT ecosystem. Therefore, this study develops a new Blockchain Assisted Data Edge Verification with consensus algorithm for Machine Learning (BDEV-CAML) technique for IoT Fault Detection purposes. The presented BDEV-CAML technique integrates the benefits of blockchain, IoT, and ML models to enhance the IoT network's trustworthiness, efficacy, and security. In BC technology, IoT devices that possess a significant level of decentralized decision-making capability can attain a consensus on the efficiency of intrablock transactions. For fault detection in the IoT network, the deep directional gated recurrent unit (DBiGRU) model is used. Finally, the African vulture optimization algorithm (AVOA) technique is utilized for the optimal hyperparameter tuning of the DBiGRU model, which helps in improving the fault detection rate. A detailed set of experiments were carried out to highlight the enhanced performance of the BDEV-CAML algorithm. The comprehensive experimental results stated the improved performance of the BDEV-CAML technique over other existing models with maximum accuracy of 99.6%.

关键词： Internet of Things Fault detection Logic gates Blockchains Security Tuning consensus algorithm Blockchain consensus algorithm fault detection deep learning hyperparameter tuning

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Cs-pbft: a comprehensive scoring-based Practical Byzantine Fault Tolerance consensus algorithm

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JOURNAL OF SUPERCOMPUTING 2025年第7期81卷 1-32页

作者： Liang, Bo Yuan, Fujiang Deng, Jiaru Wu, Qi Gao, Jie Taiyuan Normal Univ Sch Comp Sci & Technol Jinzhong 030619 Shanxi Peoples R China Shanxi Key Lab Intelligent Optimizat Comp & Blockc Jinzhong 030619 Shanxi Peoples R China Shanxi Vocat Univ Engn Sci & Technol Sch Intelligent Mfg Jinzhong 030619 Shanxi Peoples R China

Practical Byzantine Fault Tolerance (PBFT) is one of the most important consensus algorithms in distributed systems, which can effectively respond to the threat of malicious nodes. However, PBFT still has shortcomings in terms of arbitrary selection of primary nodes, high communication overhead, and lack of reward and punishment mechanisms. To address this problem, in this paper, we propose a comprehensive scoring-based Practical Byzantine Fault Tolerance consensus algorithm, called CS-PBFT. The algorithm introduces a comprehensive scoring mechanism to evaluate the node's reliability and overall capability, which is composed of two key metrics: node honor and recommendation scores. Based on this mechanism, the algorithm selects the primary node, slave node, and alternate node to ensure an efficient and secure consensus process. Additionally, the algorithm optimizes the communication process in the Commit and Reply phases of the PBFT consensus protocol, reducing communication latency and improving consensus efficiency. Experimental results show that the improved PBFT algorithm not only improves consensus efficiency but also reduces communication overhead, strengthens fault tolerance against malicious nodes, and demonstrates better scalability.

关键词： Blockchain PBFT consensus algorithm CS-PBFT

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