Proposed Consensus Protocol Research Articles

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

In this paper, we propose hybrid consensus algorithms that combine machine learning (ML) techniques to address the challenges and vulnerabilities in blockchain networks. Consensus Protocols make ensuring agreement among the applicants in the distributed systems difficult. However, existing mechanisms are more vulnerable to cyber-attacks. Previous studies extensively explore the influence of cyber attacks and highlight the necessity for effective preventive measures. This research presents the integration of ML techniques with the proposed hybrid consensus algorithms and advantages over predicting cyber-attacks, anomaly detection, and feature extraction. Our hybrid approaches leverage and optimize the proposed consensus protocols' security, trust, and robustness. However, this research also explores the various ML techniques with hybrid consensus algorithms, such as Delegated Proof of Stake Work (DPoSW), Proof of Stake and Work (PoSW), Proof of CASBFT (PoCASBFT), Delegated Byzantine Proof of Stake (DBPoS) for security enhancement and intelligent decision making in consensus protocols. Here, we also demonstrate the effectiveness of the proposed methodology within the decentralized networks using the ProximaX blockchain platform. This study shows that the proposed research framework is an energy-efficient mechanism that maintains security and adapts to dynamic conditions. It also integrates privacy-enhancing features, robust consensus mechanisms, and ML approaches to detect and prevent security threats. Furthermore, the practical implementation of these ML-based hybrid consensus models faces significant challenges, such as scalability, latency, throughput, resource requirements, and potential adversarial attacks. These challenges must be addressed to ensure the successful implementation of the blockchain network for real-world scenarios.

Adaptive Fuzzy Prescribed-Time Connectivity-Preserving Consensus of Stochastic Nonstrict-Feedback Switched Multiagent Systems

An adaptive fuzzy prescribed-time connectivitypreserving consensus protocol is designed for a class of stochastic nonstrict-feedback multiagent systems, in which periodic disturbances, switched nonlinearities, input saturation and limited communication ranges are taken into consideration simultaneously. The connectivity, determined by the limited communication ranges and initial positions of agents, is preserved by incorporating an error transformation. Further, common Lyapunov function is considered to deal with the switching modes. By combining reduced fuzzy logic system with Fourier series expansion, a novel approximator is constructed to deal with periodically disturbed nonlinearities and to surmount the difficulty brought by the nonstrict-feedback structure. More importantly, distinctly from the existing finite/fixed-time control strategies where the settling time is heavily dependent on the accurate value of the initial states and control parameters, the settling time of the proposed prescribed-time consensus is completely independent of the initialization and control parameters and can be given a priori only according to actual demands. Based on the Lyapunov stability theory, the designed controller ensures that the connectivity-preserving consensus is achieved in prescribed time and all the signals remain bounded in probability. To the end, the feasibility of the proposed consensus protocol is demonstrated by simulation.

Adaptive consensus of second‐order nonlinear MASs with aperiodically time‐varying parameters and unknown control directions

AbstractThe problem of adaptive consensus is addressed for a class of second‐order nonlinear multi‐agent systems with aperiodically time‐varying parameters and unknown control directions. Firstly, a new adaptive control approach, so‐called congelation of variables method, is adopted to deal with aperiodically time‐varying parameters which are fast‐varying in an unknown compact set with only their radii known a priori. Secondly, a novel Nussbaum‐type function approach is utilized to address the problem of unknown control directions. It is noteworthy that the control directions investigated in this paper are allowed to be completely unknown and nonidentical, whereas the unknown control directions in the most existing works are assumed to be identical. Thirdly, the unknown nonlinear function in each follower's dynamics is approximated by radial basis function neural network approximation technique. The approximation error, external disturbance in the follower's dynamics, as well as the leader's unknown acceleration dynamics are suppressed as an adaptive robust term, which can alleviate the online computational burden. Then, by designing time‐varying control gains updated adaptively with only local information, a fully distributed adaptive consensus control scheme is designed to guarantee that the multi‐agent systems achieve consensus asymptotically in the presence of unknown aperiodically time‐varying parameters, unknown nonidentical control directions, unknown nonlinearities, and external disturbances. Two simulation examples are provided to validate the effectiveness of the proposed consensus protocol.

Machine-Learning-Enhanced Blockchain Consensus With Transaction Prioritization for Smart Cities

In the given technology-driven era, smart cities are the next frontier of technology, and these smart cities aim to improve the quality of people’s lives. In this article, we introduce such future Internet of Things (IoT)-based smart cities that leverage blockchain technology. Particularly, when there are multiple parties involved, blockchain helps in improving the security and transparency of the system in an efficient manner. However, if a current fee-based or first-come–first-serve-based processing is used, emergency events may get delayed and even threaten people’s lives. Thus, there is a need for transaction prioritization based on the priority of information and a dynamic block creation mechanism for efficient data recording and faster event response. Also, our system focuses on the consortium blockchain maintained by a group of members working across different organizations to provide more efficiency. The leader election procedure in such a consortium blockchain becomes more important for the transaction prioritization process to take place honestly. Hence, in our proposed consensus protocol, we deploy a machine-learning (ML) algorithm to achieve efficient leader election, based on which a novel dynamic block creation algorithm is designed. Also, to ensure the honest block generation behavior of the leader, a peer-prediction-based verification mechanism is proposed. Both security analysis and simulation experiments are carried out to demonstrate the robustness, accuracy, and efficiency of our proposed scheme.

SIM-P—A Simplified Consensus Protocol Simulator: Applications to Proof of Reputation-X and Proof of Contribution

Blockchain is a distributed ledger in which participating users with varying levels of trust agree on the ledger’s content using a consensus mechanism called consensus protocols. There has been a rising interest in the design of consensus protocols since they play a central role in blockchain architecture. However, many recently proposed consensus protocols lack experimental verification which hampers the possible deployment of these protocols in real-world blockchain networks. In this article, we propose a simple tool called simplified consensus protocol simulator (SIM-P) that can accurately simulate the behavior of these consensus protocols with ease. It is an agent-based stochastic simulator that relies on the sequential Monte Carlo method to model how block publishers are selected. The likelihood of each node (represented as agents) being selected as a block publisher is represented by independent trials in a binomial experiment. We provide a base SIM-P model that simulates Proof of Work (PoW) for benchmarking purposes. The PoW model also serves as the basic structure of the simulator that can be adapted to other protocols. We showcase the flexibility of SIM-P by proposing two additional simulation models for Proof of Reputation-X and Proof of Contribution, both of which lack experimental verification in their original design specifications. We show how the simulator can be used to produce vital metrics, such as throughput, resistance against the 51% attack, and energy consumption. We verify the accuracy of SIM-P by comparing PoW’s simulated results with theoretical estimates and historical Bitcoin data.

Consensus Protocol for Discrete-Time Linear Multiagent Systems With Channel Fadings: A Dynamic Event-Based Approach

This article investigates the consensus problem of discrete-time linear multiagent systems with channel fadings over wireless sensor networks. The phenomena of channel fadings are described as the stochastic Rice fading model with random time-varying channel coefficients. By utilizing the local state information and constructing a dynamic auxiliary system, a novel control protocol with the dynamic discrete-time event-triggered scheme has been proposed. Sufficient conditions are obtained to guarantee the asymptotic consensus of the multiagent systems under the proposed protocol. Compared with the existing works related to discrete-time event-triggered consensus, the interevent time between any two successive events can be prolonged, and thus, the transmission data packages can be decreased immensely. Finally, the effectiveness of the proposed consensus protocol with a dynamic discrete-time event-triggered scheme is testified by numerical simulations.

Adaptive fuzzy connectivity-preserving consensus protocols for stochastic strict-feedback nonlinear MASs subject to unmeasured periodic disturbances

Two adaptive fuzzy connectivity-preserving consensus control schemes, in continuous and event-triggered manners, are proposed for stochastic strict-feedback nonlinear multi-agent systems subject to unmeasured periodic disturbances. Differently from the existing works on connectivity-preserving consensus where the deterministic dynamics are investigated, stochastic multi-agent systems are considered. An error transformation is incorporated to preserve the initial interaction pattern determined by initial positions and communication ranges of the agents. Moreover, the stochastic system model suffers from unmeasured periodic disturbances in a nonlinear manner. By associating Fourier series expansion with fuzzy logic system, a novel function approximator is constructed to describe the packaged disturbance-dependent nonlinear functions. Meanwhile, a nonlinear filter is designed to avert the ”explosion of complexity” problem in conventional backstepping recursive design procedure. In addition, the proposed continuous controller is developed to event-triggered one. Then, it is proved that the consensus is achieved and the initial connectivity of communication graph is preserved in the sense of probability. In simulations, two examples are provided to substantiate the effectiveness of the proposed consensus protocols.

Fully Distributed Consensus of Switched Heterogeneous Nonlinear Multi-Agent Systems With Bouc-Wen Hysteresis Input

This paper studies the adaptive fully distributed consensus problem for a class of nonlinear multi-agent systems (MASs) whose structures are heterogeneous, where agents with first-order dynamics and second-order dynamics exist simultaneously. Moreover, each agent subjects to Bouc-Wen hysteresis input. Due to the changes of the internal and external environment, all agents are considered to possess multiple modes and display the switching characteristic. To achieve the consensus tracking control of the considered MAS, first, the totally unknown nonlinear functions representing the system uncertainties are approximated by utilizing radial basis function neural networks (RBFNNs). Then, an adaptive neural consensus control protocol, which can enable the consensus objective to be achieved for the MAS, is designed via using the fully distributed design scheme and adaptive neural control method. It is noted that the information on the number of agents and the interaction topology is not required during the protocol design. Based on the Lyapunov stability theory, the proposed consensus protocol can ensure all signals of the considered MAS is bounded. Finally, simulation results are presented to show the feasibility and effectiveness of the proposed consensus protocol.

Leader-following almost output consensus for discrete-time heterogeneous multi-agent systems in the presence of external disturbances

In this paper, we consider the problem of leader-following almost output consensus for discrete-time multi-agent systems with heterogeneous follower agents. Conditions on agent dynamics, the communication topology and how the disturbance enters the agent dynamics are established under which leader-following almost output consensus can be achieved, that is, the leader-following output consensus can be reached with any pre-specified level of accuracy and the effect of the disturbance on the leader-following consensus can be attenuated to any pre-specified level. A family of state feedback consensus protocols are constructed by using the low gain feedback design technique and a modified discrete-time Riccati equation. These consensus protocols are shown to achieve leader-following almost output consensus. Additional conditions are identified under which output feedback results are established. Simulation results demonstrate the effectiveness of the proposed consensus protocols.

Finite‐time attitude consensus control for multiple rigid spacecraft based on distributed observers

The problem of attitude consensus control is addressed for multiple rigid spacecraft under a fixed interaction network where only a subset of followers can obtain the leader's state information. To estimate the attitude and angular velocity of the leader, a group of distributed finite-time observers is constructed for each follower. Then fast non-singular terminal sliding mode attitude controllers are proposed for followers based on the observed information. Rigorous proofs are presented to show the finite-time attitude consensus performance of the closed-loop multiple rigid spacecraft systems under the proposed consensus protocol including distributed observers and attitude controllers. Numerical simulations are provided to illustrate the performance of the proposed attitude consensus protocol.

A Hierarchy Byzantine Fault Tolerance Consensus Protocol Based on Node Reputation.

A blockchain has been applied in many areas, such as cryptocurrency, smart cities and digital finance. The consensus protocol is the core part of the blockchain network, which addresses the problem of transaction consistency among the involved participants. However, the scalability, efficiency and security of the consensus protocol are greatly restricted with the increasing number of nodes. A Hierarchy Byzantine Fault Tolerance consensus protocol (HBFT) based on node reputation has been proposed. The two-layer hierarchy structure is designed to improve the scalability by assigning nodes to different layers. Each node only needs to exchange messages within its group, which deducts the communication complexity between nodes. Specifically, a reputation model is proposed to distinguish normal nodes from malicious ones by a punish and reward mechanism. It is applied to ensure that the malicious node merely existing in the bottom layer and the communication complexity in the high layer can be further lowered. Finally, a random selection mechanism is applied in the selection of the leader node. The mechanism can ensure the security of the blockchain network with the characteristics of unpredictability and randomicity. Some experimental results demonstrated that the proposed consensus protocol has excellent performance in comparison to some state-of-the-art models.

Distributed consensus control for networked Euler–Lagrange systems over directed graphs: A dynamic event‐triggered approach

AbstractThis paper considers the distributed dynamic event‐triggered consensus problem of multi‐agent systems with Euler–Lagrange dynamics over directed graphs in the presence of uncertain disturbances. To achieve consensus, a dynamic triggering law is designed such that consensus of reference model can be achieved. Different from the static triggering mechanism, an extra variable is involved in the proposed dynamic triggering law, which benefits the exclusion of the Zeno behavior. Then, an auxiliary variable is introduced to simplify agent dynamics, which benefits the controller design. Based on the auxiliary variable, a local controller is further proposed to guarantee the tracking ability of the auxiliary variable to the reference model. Owing to this treatment, consensus of agents can be reached in the presence of external disturbances. In addition, no continuous communication is needed in either controller updates or triggering detection. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed consensus protocol and its advantage in reducing the communication overhead compared with the relevant static triggering mechanism.

Robust finite-time consensus control for Euler–Lagrange multi-agent systems subject to switching topologies and uncertainties

Euler–Lagrange (EL) system is a typical nonlinear system widely used to model robot systems. Although consensus of EL multi-agent systems has been extensively studied in recent years, how to achieve better consensus performance under constraints such as switching topologies and uncertainties is still an open issue. Aiming at fast convergence and effective disturbance rejection, this paper studies the integral sliding mode control problem for robust finite-time consensus of EL multi-agent systems subject to switching topologies and uncertainties. A basic integral sliding mode control (SMC) scheme is first presented for finite-time consensus of EL multi-agent systems subject to undirected topologies and uncertainties. It is shown that the proposed consensus protocol reaches good disturbance rejection and achieves robust finite-time consensus while avoiding the singularity problem in the existing studies. The proposed integral sliding mode control scheme is further extended to finite-time consensus of EL multi-agent systems subject to directed and switching topologies. Compared with the existing algorithms, faster finite-time convergence is achieved. In the simulation studies, the obtained results demonstrate the effectiveness and efficiency of the proposed algorithm.

A Dynamic Gain Approach to Consensus Control of Nonlinear Multiagent Systems With Time Delays

This article proposes a dynamic gain approach for investigating the leader-follower consensus problem of nonlinear multiagent systems with both distributed delays and discrete delays. It is assumed that each agent is in the strict-feedback form and satisfies the Lipschitz condition with an unknown constant. A novel dynamic gain observer is first constructed for each follower by only utilizing the output information of the follower and its neighbors. By introducing an observer, a distributed output-feedback control protocol is designed for each follower agent under a directed communication topology. It is proved by the Lyapunov-Razumikhin theorem that the consensus of the multiagent system is achieved with the proposed consensus protocol. Different from the existing results, the dynamic gain is constructed for each follower to propose the consensus protocol, without resorting to the celebrated backstepping technique. Moreover, the time-varying gain is designed in a uniform framework. The effectiveness of the proposed approaches is illustrated by a simulation example.

Nonfragile consensus of nonlinear multiagent systems with intrinsic delays via aperiodic memory sampled‐data control

AbstractThis paper focuses on the consensus issue of nonlinear multiagent systems (MASs) with intrinsic time‐varying delays via the nonfragile and aperiodic memory sampled‐data control scheme. An improved continuous Lyapunov–Krasovskii functional (LKF) with some two‐sided looped‐functional terms is introduced, in which several free‐weighting‐matrices are not necessarily positive definite. Furthermore, based on the property of Laplacian matrix, the consensus issue of original MASs can be investigated directly without transforming into error systems. Then, several sufficient criteria for the consensus of MASs are presented by means of the recently developed generalized integral inequality and the constructed LKF. Next, the required nonfragile controller gain is obtained by resorting to linear matrix inequalities and the maximal length of sampling period is derived as well. Finally, two illustrative examples are employed to exhibit the effectiveness and feasibility of the proposed consensus protocol.

Consensus tracking for singular multi‐agent systems with Lipschitz nonlinear dynamics and external disturbances

AbstractThe consensus tracking control problem for singular multi‐agent systems (SMASs) with Lipschitz nonlinearities and unknown disturbances is investigated. An extended state observer using only the relative output information is introduced and then a distributed consensus protocol is proposed, whose performance is analyzed using matrix analysis, singular system theory and Lyapunov stability theory. Sufficient conditions for ensuring consensus tracking with disturbance rejection of linear and Lipschitz nonlinear SMASs are, respectively, obtained under directed networks. Specifically, an equivalent formulation of achieving consensus tracking for SMASs is established, and the design procedures of gain matrices in the proposed consensus protocols are presented by the linear matrix inequality solver. Finally, simulation examples are provided to illustrate the theoretical results.

Delegated Proof of Secret Sharing: A Privacy-Preserving Consensus Protocol Based on Secure Multiparty Computation for IoT Environment

With the rapid advancement and wide application of blockchain technology, blockchain consensus protocols, which are the core part of blockchain systems, along with the privacy issues, have drawn much attention from researchers. A key aspect of privacy in the blockchain is the sensitive content of transactions in the permissionless blockchain. Meanwhile, some blockchain applications, such as cryptocurrencies, are based on low-efficiency and high-cost consensus protocols, which may not be practical and feasible for other blockchain applications. In this paper, we propose an efficient and privacy-preserving consensus protocol, called Delegated Proof of Secret Sharing (DPoSS), which is inspired by secure multiparty computation. Specifically, DPoSS first uses polynomial interpolation to select a dealer group from many nodes to maintain the consensus of the blockchain system, in which the dealers in the dealer group take turns to pack the new block. In addition, since the content of transactions is sensitive, our proposed design utilizes verifiable secret sharing to protect the privacy of transmission and defend against the malicious attacks. Extensive experiments show that the proposed consensus protocol achieves fairness during the process of reaching consensus.

Formal Modeling and Verification of a Blockchain-Based Crowdsourcing Consensus Protocol

Crowdsourcing is an effective technique that allows humans to solve complex problems that are hard to accomplish by automated tools. Some significant challenges in crowdsourcing systems include avoiding security attacks, effective trust management, and ensuring the system’s correctness. Blockchain is a promising technology that can be efficiently exploited to address security and trust issues. The consensus protocol is a core component of a blockchain network through which all the blockchain peers achieve an agreement about the state of the distributed ledger. Therefore, its security, trustworthiness, and correctness have vital importance. This work proposes a Secure and Trustworthy Blockchain-based Crowdsourcing (STBC) consensus protocol to address these challenges. Model checking is an effective and automatic technique based on formal methods that is utilized to ensure the correctness of STBC consensus protocol. The proposed consensus protocol’s formal specification is described using Communicating Sequential Programs (CSP#). Safety, fault tolerance, leader trust, and validators’ trust are important properties for a consensus protocol, which are formally specified through Linear Temporal Logic (LTL) to prevent several security attacks, such as blockchain fork, selfish mining, and invalid block insertion. Process Analysis Toolkit (PAT) is utilized for the formal verification of the proposed consensus protocol.

Resilient Distributed Multiagent Control for AC Microgrid Networks Subject to Disturbances

In actual microgrids (MGs) networks, the information exchange between distributed energy resources (DERs) agents may be subject to various types of measurement noises and effected by communication time delays. This article proposes a resilient distributed multiagent control scheme for ac MG networks subject to additive noise and time-delay disturbances. The proposed multiagent control scheme is composed of three distributed consensus protocols, which is able to synchronize the output voltages and frequencies of inverter-based DERs to their reference values and achieve the optimal active power-sharing property by a low bandwidth communication network with noise and time-delay disturbances in almost sure convergence. By means of the stochastic analysis tools and algebraic graph theory, distributed consensus control protocols are designed to be employed for the secondary control level of MGs. On this basis, we deduce the stability criteria of the closed-loop MG system under noise and time-delay disturbances. As a result, the proposed consensus protocols can well restore the voltage and frequency’s derivation produced at the primary control level, meanwhile, can well achieve the optimal power sharing even though there exist communication disturbances. Several simulation scenarios on an islanded MG network are provided to verify the proposed control protocols’ performance.

Consensus of Heterogeneous Multi-Agent Systems Under Directed Topology

In this paper, the consensus problem of heterogeneous multi-agent systems under directed topology is investigated. Specifically, this system is composed of three classes of agents respectively described by first-order, second-order and third-order integrator dynamics. By the aid of linear filter, graph theory and matrix theory, the consensus problem is realized based on the two proposed consensus protocols. Moreover, group consensus can also be solved by adjusting parameters. Finally, some examples were presented to illustrate the theoretical results. Our study is expected to establish a more realistic model and provide a method to solve the consensus problem of heterogeneous multi-agent systems in more complex situations.