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

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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Bi-Level Optimal Strategy of Islanded Multi-Microgrid Systems Based on Optimal Power Flow and consensus algorithm

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ENERGIES 2020年第7期13卷 1537页

作者： Lyu, Zhilin Yang, Xiao Zhang, Yiyi Zhao, Junhui Guangxi Univ Coll Elect Engn Nanning 530004 Peoples R China Univ New Haven Dept Elect & Comp Engn Comp Sci West Haven CT 06516 USA

Aiming at problems of power allocation and economic scheduling for independent multi-microgrid systems, a bi-level optimization method based on optimal power flow and consensus algorithm is proposed. The novelty of the method is that an independent multi-microgrid system is divided into two layers: in the upper layer, with the predicted output range of the microgrids as the input data, each microgrid is considered as a virtual power supply or virtual load, and taking the minimum network loss as the goal, the energy mutual aid and power allocation among the microgrids are transformed into solving the optimal power flow;in the lower layer, taking the upper layer power distribution scheme as the constraint condition, considering load fluctuation and wind/solar generation uncertainty, the optimal dispatch model of the controllable distributed generator is established based on the distributed theory and the consensus algorithm of equal cost increment, and the "plug and play" of the distributed generator is also realized. An islanded multi-microgrid cluster is taken as an example to verify the economy, security, and reliability of the proposed scheme. The advantages of the scheme have been shown by the simulation example. Simulation results show that the upper-layer method not only realizes the optimal power allocation of microgrids, but also reduces the power loss of the energy mutual aid among the microgrids;through the optimal scheduling of controllable power supply in the microgrid, the lower-level scheme not only improves the economic benefit of the microgrid, but also well suppresses the negative effects of the uncertainties, prediction errors and power fault removal on the multi-microgrid system, which improves the robustness of the system.

关键词： islanded multi-microgrid system bi-level optimization optimal power flow power allocation among microgrids consensus algorithm distributed generator economic dispatch

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A New consensus algorithm for Multi-Agent Systems via Decentralized Dynamic Output Feedback

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2011年第2期63卷 309-322页

作者： Zhai, Guisheng Okuno, Shohei Imae, Joe Kobayashi, Tomoaki Shibaura Inst Technol Dept Math Sci Minuma Ku Saitama 3378570 Japan Osaka Prefecture Univ Dept Mech Engn Naka Ku Sakai Osaka 5998531 Japan

In this paper, we study a consensus problem for multi-agent systems via dynamic output feedback control. The entire system is decentralized in the sense that each agent can only obtain output information from its neighbor agents. For practical purpose, we assume that actuator limitation exists, and require that the consensus be achieved among the agents at a specified convergence rate. By using an appropriate coordinate transformation, we reduce the consensus problem on hand to solving a strict matrix inequality, and then propose to use the homotopy based method for solving the matrix inequality. It turns out that our algorithm includes the existing graph Laplacian based algorithm as a special case.

关键词： Multi-agent systems consensus algorithm Decentralized dynamic output feedback Graph Laplacian Matrix inequality Homotopy method LMI

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Enhancing the performance of permissionless blockchain networks through randomized message-based consensus algorithm

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2023年第2期16卷 499-519页

作者： Ayenew, Melak Lei, Hang Li, Xiaoyu Weizhong, Qian Abeje, Eyerusalem Xiang, Wenjia Tegene, Abebe Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Sichuan Peoples R China Addis Ababa Sci & Technol Univ Ctr Artificial Intelligence Addis Ababa 16417 Ethiopia Kotebe Educ Univ Math Addis Ababa Ethiopia

A public blockchain network ensures security, performance, and integrity through its consensus algorithm. However, most public blockchain consensus algorithms require intensive resources such as;energy, CPU, stake, and memory. Further, the incentive mechanisms of most permissionless consensus algorithms are biased towards the miners having the most resources. This paper proposes a novel, resource-efficient, and fair rewarding consensus algorithm called Proof of Fit (PoF). The PoF consensus algorithm replaces the resource-intensive computation in Proof of Work (PoW) with massage-based resource-efficient computation called fitting-competition. We estimated the average computation time by developing a peer-to-peer messaging and computing network. Then we customized a public blockchain simulation framework to assess the performance parameters of the consensus algorithm. We did several experiments and compared the simulation results of PoF with PoW, Proof of Activity (PoA), Proof of Stake (PoS), and Poof of Capacity (PoC). The simulation result shows that the PoF consensus algorithm improves throughput by 1257%, 69%, 35%, and 18%, respectively;besides, it improves security, resource efficiency, and incentive distribution.

关键词： Blockchain consensus algorithm Proof of Work Peer-to-Peer Scalability Proof of Fit

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Multiagent-Based Coordination consensus algorithm for State-of-Charge Balance of Energy Storage Unit

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COMPUTING IN SCIENCE & ENGINEERING 2018年第2期20卷 64-77页

作者： Yang, Hanqing Yin, Liangzhen Li, Qi Chen, Weirong Zhou, Lijun Southwest Jiaotong Univ Chengdu Sichuan Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu Sichuan Peoples R China

A multiagent-based coordination consensus algorithm was designed to simultaneously meet state-of-charge consensus and DC bus voltage stability requirements. A distributed energy storage system model with four batteries was built in Matlab/Simulink, and local droop control was employed to achieve the proposed algorithm. A multiagent system and agent weak communication network were constructed in the JADE platform, and the effectiveness of the proposed algorithm was verified by Simulink and JADE interactive simulation. The effect of communication delay on the system was also analyzed.

关键词： Digital Simulation Energy Storage Multi Agent Systems Power Engineering Computing Energy Storage Unit Multiagent Based Coordination consensus algorithm State Of Charge consensus DC Bus Voltage Stability Requirements Distributed Energy Storage System Model Multiagent System State Of Charge Balance Matlab Simulink Local Droop Control Agent Weak Communication Network JADE Platform JADE Interactive Simulation Information Processing Object Recognition Prediction algorithms Classification algorithms algorithm Design And Analysis Mathematical Model Intelligent Systems Multi Agent Systems Intelligent Information Processing Scientific Computing Green Computing Distributed Energy Storage System Multiagent System consensus algorithm Weak Communication Network

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A Fully Distributed Economic Dispatch Method in DC Microgrid Based on consensus algorithm

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IEEE ACCESS 2022年 10卷 119345-119356页

作者： Liu, Dan Jiang, Kezheng Yan, Linfang Ji, Xiaotong Cao, Kan Xiong, Ping Huazhong Univ Sci & Technol Sch Elect & Elect Engn State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China State Grid Hubei Elect Power Res Inst Wuhan 430074 Peoples R China State Grid Suzhou City & Energy Res Inst Suzhou 215000 Peoples R China

Uncertainties of intermittent renewables and complexities of load demands bring challenges to the optimal operation of the microgrid. This paper proposes a fully distributed method based on the consensus algorithm for solving the economic dispatch problem (EDP) of DC microgrids. The proposed distributed method is performed using a multiagent system. It only needs information from neighboring agents and does not need a central controller. A two-level control structure is adopted to realize the economic dispatch and voltage regulation simultaneously. The upper level obtains the optimal power reference of dispatchable agents and maintains the power balance of the system. The lower level performs an improved droop control to track the power reference and regulate the average bus voltage for the microgrid. The proposed method's properties and convergence are analyzed using eigenvalue perturbation theory to obtain a faster convergence speed. By designing the adjacency matrix appropriately, the proposed method can ensure the system stable when the communication topology changes. Finally, several simulations are designed to verify the effectiveness of this novel control method.

关键词： DC microgrid economic dispatch consensus algorithm renewable generation

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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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Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 65卷 26-33页

作者： Qing, Xiangyun Karimi, Hamid Reza Niu, Yugang Wang, Xingyu E China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China Univ Agder Fac Sci & Engn Dept Engn N-4898 Grimstad Norway

A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algorithm on the IEEE 14-bus and 118-bus systems. The low communication requirements and high estimation accuracy of the decentralized UKF make it an alternative solution to the multi-area power system dynamic state estimation. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Dynamic state estimation Unscented Kalman filter consensus algorithm Multi-area power system

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A consensus algorithm based on collective neurodynamic system for distributed optimization with linear and bound constraints

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NEURAL NETWORKS 2020年 122卷 144-151页

作者： Zhao, Yan Liu, Qingshan Wannan Med Coll Sch Common Courses Wuhu 241000 Peoples R China Southeast Univ Sch Math Nanjing 210096 Jiangsu Peoples R China Southeast Univ Jiangsu Prov Key Lab Networked Collect Intelligen Nanjing 210096 Jiangsu Peoples R China

In this paper, an algorithm based on collective neurodynamic system is investigated for distributed constrained convex optimization, whose objective function is a sum of smooth convex functions and non-smooth L-1-norm functions. Inspired by recent advances in distributed convex optimization, the continuous-time and discrete-time distributed optimization algorithms described by collective neurodynamic systems are proposed. In the systems, each of the smooth objective functions is allocated to each node as well as each of the L-1-norm functions. However, the L-1-norm functions are realized by projection operators. Meanwhile, each node satisfies the local linear and bound constraints. Then a connected network is constituted from all the nodes with consensus to find the optimal solutions. (c) 2019 Elsevier Ltd. All rights reserved.

关键词： Distributed optimization Collective neurodynamic system consensus algorithm Lyapunov function

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