Fault-tolerant Consensus Research Articles

A novel Byzantine fault tolerance consensus for Green IoT with intelligence based on reinforcement

To enhance the consensus performance of Blockchain in the Green Internet of Things (G-IoT) and improve the static network structure and communication overheads in the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, in this paper, we propose a Credit Reinforce Byzantine Fault Tolerance (CRBFT) consensus algorithm by using reinforcement learning. The CRBFT algorithm divides the nodes into three types, each with different responsibilities: master node, sub-nodes, and candidate nodes, and sets the credit attribute to the node. The node’s credit can be adjusted adaptively through the reinforcement learning algorithm, which can dynamically change the state of nodes. CRBFT algorithm can automatically identify malicious nodes and invalid nodes, making them exit from the consensus network. Experimental results show that the CRBFT algorithm can effectively improve the consensus network’s security. Besides, compared with the PBFT algorithm, in CRBFT, the consensus delay is reduced by about 40%, and the traffic overhead is reduced by more than 45%. This reduction is conducive to save energy and reduce emissions.

Distributed Bipartite Adaptive Event-Triggered Fault-Tolerant Consensus Tracking for Linear Multiagent Systems Under Actuator Faults.

This article considers the distributed bipartite adaptive event-triggered fault-tolerant consensus tracking issue for linear multiagent systems in the presence of actuator faults based on the output feedback control protocol. Both time-varying additive and multiplicative actuator faults are taken into account in the meantime. And the upper/lower bounds of actuator faults are not required to be known. First, the state observer is designed to settle the occurrence of unmeasurable system states. Two kinds of event-triggered mechanisms are then developed to schedule the interagent communication and controller updates. Next, with the developed event-triggered mechanisms, a novel observer-based bipartite adaptive control strategy is proposed such that the fault-tolerant control problem can be addressed. Compared with some related works on this topic, our control scheme can achieve the intermittent communication and intermittent controller updates, and the more general actuator faults and network topology are considered. It is proved that the exclusion of Zeno behavior can be realized. Finally, three illustrative examples are given to demonstrate the feasibility of the main theoretical findings.

The service architecture of Internet of things terminal connection based on blockchain technology

This work aims to explore the security convenience of Internet of things (IoT) terminals based on blockchain technology and to enrich the content of IoT terminal applications. The service architecture platform of blockchain technology is proposed for the terminal connection of IoT. First, the characteristics, performance, and fault tolerance of the consensus algorithm are introduced. Then, the construction of blockchain platform is introduced, and the blockchain system and the storage of blockchain data are designed. Next, the consensus algorithm is optimized with the proof of stake equity proof consensus and the improved consensus mechanism of the practical byzantine fault tolerance consensus, to establish a blockchain service architecture platform. Finally, the node connection service architecture and block process are verified and analyzed. The results show that the blockchain-based IoT service architecture constructed under consensus algorithm has high accuracy and safety. The achievements of this study can promote the development of blockchain technology and IoT and play a good role in promoting the combination of blockchain technology and IoT terminal.

Distributed robust fault-tolerant consensus control for a class of nonlinear multi-agent systems with intermittent communications

This paper considers the H∞ consensus problem for a class of nonlinear multi-agent systems in the presence of multiple faults, including intermittent communications and actuator faults, under the switching communication topologies. Aiming at this problem, a new distributed robust fault-tolerant controller is designed by utilizing an adaptive mechanism to remove the interference of nonlinear functions and multiple faults. Furthermore, the closed-loop system is proven to be stable by applying the topology-based average dwell time technique and the Lyapunov stability theory. Compared with existing controllers for nonlinear multi-agent systems, the developed scheme is efficient for solving the fault-tolerant H∞ consensus problem of nonlinear multi-agent systems even under the influence of intermittent communications, actuator faults, and switching communication topologies. Finally, an example based on the B747-100/200 aircraft model is given to validate the proposed control scheme’s effectiveness.

An Architecture and Performance Evaluation of Blockchain-Based Peer-to-Peer Energy Trading

Several recent studies have suggested Blockchain for Peer-to-Peer energy trading (P2P-ET) to achieve better security, privacy and fast payment settlement. Most of them however rely on either public Blockchains (which have low performance) or permissioned blockchains (which have low decentralization level and do not provide byzantine fault tolerance). Moreover, these solutions have limitations when capturing the business model of existing energy trading systems. This article proposes a Unified permissioned blockchain-based P2P-ET Architecture (UBETA) that integrates three different types of energy markets and provides a unified energy trading and payment settlement model. The UBETA system is based on an enterprise Ethereum Blockchain, known as Hyperledger Besu, and Istanbul Byzantine Fault Tolerance (IBFT) consensus algorithm. We compared the performance of the proposed IBFT-based system with three existing systems (i.e., Ethereum Clique, Ethereum Proof of Work and Hyperledger Fabric's Raft) using specific performance metrics (i.e., read/write transaction latency, read/write transaction throughput and fail rate). The experiments were carried out on a network size of up to 60 nodes and a real energy trading data set from the Western Australian energy market was used. The experiment results indicate that the IBFT-based system has 15x lower latency and nearly 2x throughput compared to existing Proof of Work based P2P-ET solutions. Moreover, the system provides better scalability and success rate than existing Raft based P2P-ET systems: the fail rate of the IBFT-based system only increased by 11% while that of Raft increased by 20% when increasing the number of nodes from 20 to 60. In addition, the proposed unified energy trading model provides lower latency and reduces the number of blockchain transactions compared to the non-unified counterpart.

Research on Practical Byzantine Fault Tolerant Consensus Algorithm Based on Blockchain

Practical Byzantine Fault-tolerant Algorithm (PBFT) is the most widely used consensus algorithm in alliance chain, which has the advantages of fault tolerance and large throughput. However, PBFT also has some problems that can’t be ignored in specific blockchain applications, such as bad behavior of master node, high network communication overhead and low system flexibility. In this paper, the improvement measures of PBFT consensus algorithm are summarized from many aspects, and then compared with traditional PBFT algorithm. Finally, the development direction and trend of PBFT algorithm are prospected, hoping to provide reference for the research and innovation of PBFT consensus algorithm in the future.

Endogenous Trusted DRL-Based Service Function Chain Orchestration for IoT

With the development of the Internet of Things, trust has become a limited factor in the integration of heterogeneous IoT networks. In this regard, we use the combination of blockchain technology and SDN/NFV to build a heterogeneous IoT network resource management model based on the consortium chain. In order to solve the efficiency problem caused by the full amount of data on the chain, we deploy light nodes and full nodes for the consortium chain. At the same time, we use the idea of identification to realize the separation of identification and resource information, build the application mode of on-chain identification and off-chain information, and realize resources endogenous trust management. We also propose a practical Byzantine fault-tolerant consensus mechanism based on reputation value to save consensus costs and improve efficiency. Combined with artificial intelligence technology, we introduce deep reinforcement learning for service function chain orchestration, and design a service function chain orchestration algorithm based on Asynchronous Advantage Actor-Critic to optimize orchestration costs. The final simulation results show that the consensus algorithm and service function chain orchestration algorithm we designed have good performance in terms of cost saving and efficiency improvement.

Blockchain mechanism with Byzantine fault tolerance consensus for Internet of Drones services

AbstractThe increasing number of drones brings various issues like security risks, increasing air traffic, misuse or crash of drones, and so on. Blockchain can provide the solution to mitigate these problems of drones. Hence, in this article, we have presented the Blockchain of Drones (BCoD), a conceptual approach of collaboration between blockchain and IoD to make drones advantageous through blockchain properties. But the main challenge for adopting blockchain is scalability as consensus in blockchain relies on the message communications by replicated nodes to attain flexibility against faulty nodes. Considering this, we present an advanced byzantine fault tolerance (ABFT) consensus for drone‐based applications. This protocol provides scalability with minimum cost and resources for achieving general agreement. It uses only f + 1 resources in normal case and 2f + 1 resources in faulty case with O(n) communication complexity. The systematic analysis and evaluation show that the ABFT improves the performance of the system for a wide range of networks compared with existing BFT systems.

Fusion Chain: A Decentralized Lightweight Blockchain for IoT Security and Privacy

As the use of internet of things (IoT) devices increases, the importance of security has increased, because personal and private data such as biometrics, images, photos, and voices can be collected. However, there is a possibility of data leakage or manipulation by monopolizing the authority of the data, since such data are stored in a central server by the centralized structure of IoT devices. Furthermore, such a structure has a potential security problem, caused by an attack on the server due to single point vulnerability. Blockchain’s, through their decentralized structure, effectively solve the single point vulnerability, and their consensus algorithm allows network participants to verify data without any monopolizing. Therefore, blockchain technology becomes an effective solution for solving the security problem of the IoT’s centralized method. However, current blockchain technology is not suitable for IoT devices. Blockchain technology requires large storage space for the endless append-only block storing, and high CPU processing power for performing consensus algorithms, while its opened block access policy exposes private data to the public. In this paper, we propose a decentralized lightweight blockchain, named Fusion Chain, to support IoT devices. First, it solves the storage size issue of the blockchain by using the interplanetary file system (IPFS). Second, it does not require high computational power by using the practical Byzantine fault tolerance (PBFT) consensus algorithm. Third, data privacy is ensured by allowing only authorized users to access data through public key encryption using PKI. Fusion Chain was implemented from scratch written using Node.js and golang. The results show that the proposed Fusion Chain is suitable for IoT devices. According to our experiments, the size of the blockchain dramatically decreased, and only 6% of CPU on an ARM core, and 49 MB of memory, is used on average for the consensus process. It also effectively protects privacy data by using a public key infrastructure (PKI).

Adaptive NN-Based Consensus for a Class of Nonlinear Multiagent Systems With Actuator Faults and Faulty Networks.

This article addresses the problem of fault-tolerant consensus control of a general nonlinear multiagent system subject to actuator faults and disturbed and faulty networks. By using neural network (NN) and adaptive control techniques, estimations of unknown state-dependent boundaries of nonlinear dynamics and actuator faults, which can reflect the worst impacts on the system, are first developed. A novel NN-based adaptive observer is designed for the observation of faulty transformation signals in networks. On the basis of the NN-based observer and adaptive control strategies, fault-tolerant consensus control schemes are designed to guarantee the bounded consensus of the closed-loop multiagent system with disturbed and faulty networks and actuator faults. The validity of the proposed adaptively distributed consensus control schemes is demonstrated by a multiagent system composed of five nonlinear forced pendulums.

Achieving IoT data security based blockchain

Security in Internet of Things (IoT) remains a significant concern within academia and industry. With the great potential of IoT data, the traditional centralized architecture of IoT system is limited and cannot afford security solutions. In this paper, to address the issue of IoT data security, we propose a blockchain-based data acquisition and processing architecture. The proposed architecture ensures IoT data security through data consistency. It supports distributed IoT nodes to negotiate consensus on the processed data, and decides to write the consensus data to blockchain ledger. Since distributed nodes are non-peer and have different voting weights in the proposed architecture, traditional consensus algorithms are not applicable. Therefore, we design a novel consensus algorithm for data consistency between non-peer nodes: Byzantine Fault-Tolerant consensus algorithm based on Dynamic Permission Adjustment (DPA-PBFT) algorithm. The DPA-PBFT algorithm works in the consensus domain of different weight nodes with the ability of self-optimize. It improves consensus efficiency and reduces communication overhead for data consistency. Finally, we conduct numerous experiments to evaluate the performance improvement of the DPA-PBFT algorithm under the proposed distributed architecture.

Private blockchain-envisioned multi-authority CP-ABE-based user access control scheme in IIoT

Recent advances in Low Power Wide Area Network (LPWAN) are expected to augment the already prodigious proliferation of Industrial Internet of Things (IIoT). However, this unrepresented growth is tinged by the uncertainty of possible challenges in security and privacy. In this work, we propose a novel blockchain-envisioned fine grained user access control scheme for data security and scalability in IIoT environment. The proposed scheme supports multiple attribute authorities and also a constant size key and ciphertext. The data gathered by the IoT smart devices are encrypted using the cipher-policy attribute based encryption (CP-ABE) and sent to their nearby gateway nodes. Later, the gateway nodes form the transactions from the encrypted data from the smart devices which are used to form partial blocks. The partial blocks are then forwarded to the cloud server(s) in the peer-to-peer (P2P) network to convert them into full blocks, which are verified, mined and added into the blockchain using the voting-based practical Byzantine fault tolerance (PBFT) consensus algorithm. The proposed scheme also allows a user to access the secure data stored in the blocks into the blockchain using the CP-ABE mechanism. The security analysis demonstrates the robustness of the proposed scheme against various attacks, and the comparative study with related relevant schemes also highlights the advantage of the proposed scheme over existing approaches. Finally, a blockchain implementation of the presented scheme summarizes the computational costs for a varied number of transactions per block, and also for a varied number of blocks mined in the blockchain.

DRBFT: Delegated randomization Byzantine fault tolerance consensus protocol for blockchains

Blockchain, as a potentially revolutionary technology, has been used in cryptocurrency to record transactions chronologically among multiple parties. Due to the fast development of the blockchain and its de-centralization, blockchain technology has been applied in broader scenarios, such as smart factories, supply chains, and smart cities. Consensus protocol plays a vital role in the blockchain, which addresses the issue of reaching consensus on transaction results among involved participants. Nevertheless, with the complexity of the network environment and growing amount of network users, the advance of blockchain is gradually restricted by the efficiency, security and reliability of consensus protocols. In this paper, we propose a delegated randomization Byzantine fault tolerance consensus protocol named DRBFT based on Practical Byzantine Fault Tolerance (PBFT) to enhance the efficiency and reliability of the consensus procedure. Specifically, a random selection algorithm called RS is developed to cooperate with the voting mechanism, which can effectively reduce the number of nodes participating in the consensus process. Our proposed scheme is characterized by the unpredictability, randomicity and impartiality, which accelerate the system to reach consensus on the premise of ensuring the system activity. Furthermore, the feasibility of our proposed scheme is also proved by both theoretical analysis and experimental evaluations.

Distributed Fault-Tolerant Consensus Tracking Control of Multi-Agent Systems Under Fixed and Switching Topologies

This paper proposes a novel distributed fault-tolerant consensus tracking control design for multi-agent systems with abrupt and incipient actuator faults under fixed and switching topologies. The fault and state information of each individual agent is estimated by merging unknown input observer in the decentralized fault estimation hierarchy. Then, two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation. Simulation results demonstrate the effectiveness of the proposed fault-tolerant consensus tracking control algorithm.

Event-triggered fault-tolerant consensus control with control allocation in leader-following multi-agent systems

Event-triggered consensus in leader-following multi-agent systems with actuator fault is considered in this paper, in which the fault investigated can be multiplicative fault and outage fault. An event-triggered mechanism is utilized to relieve the communication burden of the interconnected system. Then, control allocation is proposed to solve actuator fault in the multi-agent systems for the first time. Compared with the existing fault-tolerant methods, the proposed method can guarantee that the consensus errors converge to zero asymptotically without the traditional rank assumption. Meanwhile, the Zeno behavior of the event-triggered system is proved to be avoided. Simulation results are also provided to verify the effectiveness of the proposed method.

Concurrent Practical Byzantine Fault Tolerance for Integration of Blockchain and Supply Chain

Currently, the integration of the supply chain and blockchain is promising, as blockchain successfully eliminates the bullwhip effect in the supply chain. Generally, concurrent Practical Byzantine Fault Tolerance (PBFT) consensus method, named C-PBFT, is powerful to deal with the consensus inefficiencies, caused by the fast node expansion in the supply chain. However, due to the tremendous complicated transactions in the supply chain, it remains challenging to select the credible primary peers in the concurrent clusters. To address this challenge, the peers in the supply chain are classified into several clusters by analyzing the historic transactions in the ledger. Then, the primary peer for each cluster is identified by reputation assessment. Finally, the performance of C-PBFT is evaluated by conducting experiments in Fabric.

A blockchain-based authentication scheme for the machine-to-machine communication of a cyber physical system

Today, the manner in which we communicate has greatly advanced. The technology is not just about machines, but people with technology together. Machine-to-machine (M2M) communication is unavoidable in the Internet of things. However, at the same time, there are more attacks against the M2M system. Therefore, a reliable and secure authentication mechanism is required. Blockchain technology is decentralized and highly secure while being tamper-proof. This protects M2M service providers by eliminating the single point of failures. This paper proposes a blockchain-based authentication scheme that uses a practical Byzantine fault tolerance (pBFT) consensus mechanism for M2M security in cyber physical systems. By implementing a blockchain to an M2M system, it provides an ID for devices on the blockchain. Simulation results have shown that the data on the chain cannot be altered. A pBFT consensus algorithm also ensures that the blockchain network is able to come to a consensus with faults.

BEI‐TAB: Enabling Secure and Distributed Airport Baggage Tracking with Hybrid Blockchain‐Edge System

Global air transport carries about 4.3 billion pieces of baggage each year, and up to 56 percent of travellers prefer obtaining real‐time baggage tracking information throughout their trip. However, the traditional baggage tracking scheme is generally based on optical scanning and centralized storage systems, which suffers from low efficiency and information leakage. In this paper, a blockchain and edge computing‐based Internet of Things (IoT) system for tracking of airport baggage (BEI‐TAB) is proposed. Through the combination of radio frequency identification technology (RFID) and blockchain, real‐time baggage processing information is automatically stored in blockchain. In addition, we deploy Interplanetary File System (IPFS) at edge nodes with ciphertext policy attribute‐based encryption (CP‐ABE) to store basic baggage information. Only hash values returned by the IPFS network are kept in blockchain, enhancing the scalability of the system. Furthermore, a multichannel scheme is designed to realize the physical isolation of data and to rapidly process multiple types of data and business requirements in parallel. To the best of our knowledge, it is the first architecture that integrates RFID, IPFS, and CP‐ABE with blockchain technologies to facilitate secure, decentralized, and real‐time characteristics for storing and sharing data for baggage tracking. We have deployed a testbed with both software and hardware to evaluate the proposed system, considering the performances of transaction processing time and speed. In addition, based on the characteristics of consortium blockchain, we improved the practical Byzantine fault tolerance (PBFT) consensus protocol, which introduced the node credit score mechanism and cooperated with the simplified consistency protocol. Experimental results show that the credit score‐based PBFT consensus (CSPBFT) can shorten transaction delay and improve the long‐term running efficiency of the system.

On Performance of PBFT Blockchain Consensus Algorithm for IoT-Applications With Constrained Devices

Cyber-physical systems and the Internet of things (IoT) are becoming an integral part of the digital society. The use of IoT services improves human life in many ways. Protection against cyber threats is an utmost important prospect of IoT devices operation. Malicious activities lead to confidential data leakage and incorrect performance of devices becomes critical. Therefore, development of effective solutions that can protect both IoT devices data and data exchange networks turns in to a real challenge. This study provides a critical analysis of the feasibility of using blockchain technology to protect constrained IoT devices data, justifies the choice of Practical Byzantine Fault Tolerance (PBFT) consensus algorithm for implementation on such devices, and simulates the main distributed ledger scenarios using PBFT. In this paper we investigate typical IoT network scenarios that can disrupt system performance. To ensure the adequacy of the models under study, we have analyzed the characteristics of real constrained IoT devices in terms of computing power and data rate. The simulation results demonstrate efficiency of the blockchain technology for constrained devices and make it possible to evaluate applicability limits of the chosen consensus algorithm.

An Integrated Architecture for Maintaining Security in Cloud Computing Based on Blockchain

Due to its wide accessibility, cloud services are susceptible to attacks. Data manipulation is a serious threat to data integrity which can occur in cloud computing – a relatively new offering under the umbrella of cloud services. Data can be tampered with, and malicious actors could use this to their advantage. Cloud computing clients in various application domains want to be assured that their data is accurate and trustworthy. On another spectrum, blockchain is a tamper-proof digital ledger that can be used alongside cloud technology to provide a tamper-proof cloud computing environment. This paper proposes a scheme that combines cloud computing with blockchain that assures data integrity for all homomorphic encryption schemes. To overcome the cloud service provider’s (CSP) ultimate authority over the data, the proposed scheme relies on the Byzantine Fault Tolerance consensus to build a distributed network of processing CSPs based on the client requirements. After certain computations performed by all CSPs, they produce a master hash value for their database. To ensure immutable data is produced, master hash values are preserved in Bitcoin or Ethereum blockchain networks. The master hash values can be obtained by tracking the block header address for verification purposes. A theoretical analysis of the overhead costs associated with creating master hash values for each of the cryptocurrencies is presented. We found that Ethereum leads to lower client financial costs and better online performance than Bitcoin. We also specify the data security requirements the proposed scheme provides, the ground-level implementation, and future work. The proposed verification scheme is based on public cryptocurrency as a back-end service and does not require additional setup actions by the client other than a wallet for the chosen cryptocurrency.