Practical Byzantine Fault Tolerance Research Articles

DRL-Based V2V Computation Offloading for Blockchain-Enabled Vehicular Networks

Vehicular edge computing (VEC) is an effective method to increase the computing capability of vehicles, where vehicles share their idle computing resources with each other. However, due to the high mobility of vehicles, it is challenging to design an optimal task allocation policy that adapts to the dynamic vehicular environment. Further, vehicular computation offloading often occurs between unfamiliar vehicles, how to motivate vehicles to share their computing resources while guaranteeing the reliability of resource allocation in task offloading is one main challenge. In this paper, we propose a blockchain-enabled VEC framework to ensure the reliability and efficiency of vehicle-to-vehicle (V2V) task offloading. Specifically, we develop a deep reinforcement learning (DRL)-based computation offloading scheme for the smart contract of blockchain, where task vehicles can offload part of computation-intensive tasks to neighboring vehicles. To ensure the security and reliability in task offloading, we evaluate the reliability of vehicles in resource allocation by blockchain. Moreover, we propose an enhanced consensus algorithm based on practical Byzantine fault tolerance (PBFT), and design a consensus nodes selection algorithm to improve the efficiency of consensus and motivate base stations to improve reliability in task allocation. Simulation results validate the effectiveness of our proposed scheme for blockchain-enabled VEC.

Practical Byzantine Fault Tolerance Based Robustness for Mobile Crowdsensing

Mobile crowdsensing (MCS) has become a prominent paradigm to collect and share data based on sensing devices with built-in sensors in the Internet of Things era. Nevertheless, conventional MCS confronts various security and privacy vulnerabilities in terms of decentralized, openness, and non-dedicated properties. Currently, the submitted tasks are collected and managed conventionally by a centralized MCS platform. A centralized MCS platform is not safe enough to protect and prevent tampering sensing tasks since it confronts the single point of failure, which reduces the effectiveness and robustness of the MCS system. Meanwhile, fake task attack is a serious threat, as it would drain excessive resources from the participant devices and clog the MCS servers to disrupt the services offered by the MCS. To address the centralized issue and identify fake tasks, a blockchain-based decentralized MCS is designed. Integration of blockchain into MCS enables a decentralized framework. Moreover, the distributed nature of a blockchain chain prevents sensing tasks from being tampered. The blockchain uses a practical Byzantine fault tolerance consensus that can tolerate one-third faulty nodes, making the implemented MCS system robust and sturdy. In addition, an ensemble learning approach is deployed in the blockchain for eliminating fake tasks by malicious requesters. The evaluation test is conducted under two different datasets representing a big city and a small one to have an MCS campaign. Numerical results show that the ensemble approach eliminates most of the fake tasks with a detection accuracy of up to 0.99. Furthermore, the ensemble learning integrated system outperforms individual learner based centralized systems, and non-fault tolerant systems in terms of Ratio of Legitimate Tasks (RoLT) saved and Ratio of Fake Tasks (RoFT).RoFTis low to 0.01, andRoLTis high up to 0.913 via the proposed MCS blockchain-driven framework.

Wireless Distributed Consensus in Vehicle to Vehicle Networks for Autonomous Driving

Vital societal and industrial autonomous components are increasingly interconnected through communication networks to complete critical tasks cooperatively. However, as the reliability and trust requirements for connected autonomous systems continue to grow, the centralized communication and decision approaches that are in use today are reaching their limits. Focusing on autonomous driving applications, this paper proposes a resilient and trustworthy framework on wireless distributed consensus networks, where the communication links are less reliable or are even in the presence of incorrect local sensor readings/decisions. To accomplish that, a novel three stages consensus mechanism is proposed based on the practical Byzantine fault tolerance (PBFT), where the veto collection and gossip stages are designed to meet the stringent and complex requirements for a vehicle's maneuvers. A plan tree synthesis is also proposed to make consensus on a series of decisions while adopting network members' decision preferences. A detailed protocol including the distributed consensus, plan tree synthesis, dynamic grouping, etc. is proposed. Simulation results show that the proposed consensus mechanism is able to be reached and propagated through the network under poor wireless communication conditions and the presence of faulty vehicles with incorrect sensor readings. The result can be extended to other autonomous systems to significantly enhance safety in critical industrial applications.

Toward Trusted Unmanned Aerial Vehicle Swarm Networks: A Blockchain-Based Approach

The unmanned aerial vehicle (UAV) swarm is widely applied in many fields, such as disaster relief and geological exploration. However, it is highly vulnerable when facing an attack from internal malicious UAVs due to the underlying disconnected, intermittent, and limited (DIL) network environment. Recently, building trusted networks has been considered as a strategy to address security issues. Nevertheless, deploying a trusted network in a swarm faces many challenges imposed by the dynamic topology and limited resources of DIL networks. In order to overcome these challenges, we developed a blockchain-based UAV trusted self-organizing networking mechanism (BC-UTSON) to enhance internal security. Three key technologies are proposed for assisting BC-UTSON in achieving trustworthiness. UAV practical Byzantine fault tolerance (U-PBFT) is proposed to guarantee the lightweight consensus and real-time full-node trustworthiness evaluation under the hierarchical self-organizing networking structure of a UAV swarm. A blockchain-based multiweighted subjective logic (BMWSL) scheme has been designed to identify malicious UAV nodes based on the trustworthiness evaluation, which also assists the trusted path quality-aware dynamic routing (TPDR) mechanism to prevent data from routing through malicious nodes. The experimental results show that the proposed BC-UTSON performs much better than nonblockchain-based mechanisms for the UAV swarm.

Antiquantum Privacy Protection Scheme in Advanced Metering Infrastructure of Smart Grid Based on Consortium Blockchain and RLWE

Smart meters in advanced metering infrastructure (AMI) collect fine-grained, real-time power consumption data may result in user privacy leakage. Aiming at the problem that existing privacy protection schemes cannot resist quantum attacks, an antiquantum privacy protection scheme in AMI of smart grid based on consortium blockchain and ring learning with errors (RLWE) is proposed. The scheme has the following contributions. First, the RLWE-based secure communication scheme is designed in this article, which ensures the resistance of the scheme to quantum attacks. Second, all smart meters in AMI use anonymous identity to communicate with the control center, and the fine-grained power consumption data is also encrypted and digitally signed to prevent user privacy leakage and tampering of power consumption data. And the scheme does not use bilinear pairings and exponential operations and has efficient computational performance. Third, a two-tier consortium blockchain storage system consisted of regional gateways and data aggregators are designed to eliminate the single point of failure problems of the data aggregators. The practical byzantine fault tolerance consensus mechanism is improved to reduce the communication cost in the consensus process. The scheme's security is proven theoretically, and the experimental results show that the scheme has a low computational cost.

Anti-Counterfeiting and Traceability Consensus Algorithm Based on Weightage to Contributors in a Food Supply Chain of Industry 4.0

Supply chain management can significantly benefit from contemporary technologies. Among these technologies, blockchain is considered suitable for anti-counterfeiting and traceability applications due to its openness, decentralization, anonymity, and other characteristics. This article introduces different types of blockchains and standard algorithms used in blockchain technology and discusses their advantages and disadvantages. To improve the work efficiency of anti-counterfeiting traceability systems in supply chains and reduce their energy consumption, this paper proposes a model based on the practical Byzantine fault tolerance (PBFT) algorithm of alliance chains. This model uses a credit evaluation system to select the primary node and integrates the weightage to contributors (WtC) algorithm based on the consensus mechanism. This model can reduce the decline in the algorithm success rate while increasing the number of malicious transaction nodes, thereby reducing the computing cost. Additionally, the throughput of the algorithmic system increases rapidly, reaching approximately 680 transactions per second (TPS) in about 120 min after the malicious nodes are eliminated. The throughput rapidly increases as the blacklist mechanism reduces the number of malicious nodes, which improves the system’s fault tolerance. To validate the effectiveness of the proposed model, a case study was conducted using data from the anti-counterfeiting traceability system of the real-life supply chain of a food company. The analysis results show that after a period of stable operation of the WtCPBFT algorithm in the proposed model, the overall communication cost of the system was reduced, the throughput and stability were improved, and the fault-tolerant performance of the system was improved. In conclusion, this paper presents a novel model that utilizes the PBFT algorithm of alliance chains and the WtC algorithm to improve the efficiency and security of anti-counterfeiting traceability systems in supply chains. The results of the case study indicate that this model can effectively reduce communication costs, improve throughput and stability, and enhance the fault tolerance of the system.

Blockchain-Based Double-Layer Byzantine Fault Tolerance for Scalability Enhancement for Building Information Modeling Information Exchange

A Practical Byzantine Fault Tolerance (PBFT) is a consensus algorithm deployed in a consortium blockchain that connects a group of related participants. This type of blockchain suits the implementation of the Building Information Modeling (BIM) information exchange with few participants. However, when much more participants are involved in the BIM information exchange, the PBFT algorithm, which inherently requires intensive communications among participating nodes, has limitations in terms of scalability and performance. The proposed solution for a multi-layer BFT hypothesizes that multi-layer BFT reduces communication complexity. However, having more layers will introduce more latency. Therefore, in this paper, Double-Layer Byzantine Fault Tolerance (DLBFT) is proposed to improve the blockchain scalability and performance of BIM information exchange. This study shows a double-layer network structure of nodes that can be built with each node on the first layer, which connects and forms a group with several nodes on the second layer. This network runs the Byzantine Fault Tolerance algorithm to reach a consensus. Instead of having one node send messages to all the nodes in the peer-to-peer network, one node only sends messages to a limited number of nodes on Layer 1 and up to three nodes in each corresponding group in Layer 2 in a hierarchical network. The DLBFT algorithm has been shown to reduce the required number of messages exchanged among nodes by 84% and the time to reach a consensus by 70%, thus improving blockchain scalability. Further research is required if more than one party is involved in multi-BIM projects.

Blockchain-Based Information Sharing Security for the Internet of Things

The Blockchain (BCT) is the first decentralized ledger to include a trust mechanism in its design. It establishes a trustworthy framework for distributed commands by using data redundancy at several nodes. Conspicuously, the current study presents a BCT-based lightweight IoT information exchange security architecture for data exchange. The proposed technique uses a dual chain methodology, namely transaction and data BCT working together to provide distributed storage and tamper-proofing of data. Moreover, Transaction BCT is enhanced by a consensus algorithm using a practical Byzantine fault-tolerant (PBFT) mechanism. The proposed algorithm can increase data registering efficiency, transactions, and privacy protection BCT. It is deduced that local dominance can be avoided using the dynamic game strategy of node cooperation. Furthermore, by reporting the node’s global reputation value, the status of the unknown node may be approximated. The high-trust measure is utilized to adjust the weight of the affected node in the combined node-set, leading to the Bayesian equilibrium. The proposed model is validated in several experimental simulations and results are compared with state-of-the-art techniques. Based on the results, enhanced performance is registered for the proposed techniques in terms of temporal delay, statistical efficiency, reliability, and stability.

Wireless Distributed Consensus for Connected Autonomous Systems

Connected critical autonomous systems (C-CAS) are envisioned to significantly change our life and work styles through emerging vertical applications such as autonomous vehicles and cooperative robots. However, as the scale of the connected nodes continues to grow, their heterogeneity and cyber-security threats are more eminent, and conventional centralized communications and decision-making methodology are reaching their limit. This paper is the first exploration of a trustworthy and fault-tolerant framework for C-CAS for achieving hyper-reliable global decision-making in a trustless environment, where the connected sensors/nodes are less reliable due to either communication failure or local decision error (e.g., by sensing algorithm/AI, etc.). The proposed framework is based on two iconic distributed consensus (DC) mechanisms, practical Byzantine fault tolerance (PBFT) and Raft, under the proposed PICA (Perception-Initiative-Consensus-Action) protocol with wireless connections among the nodes. We first analytically derived consensus reliability in six different system models. The other fundamental performance metrics such as the consensus throughput and latency, node scalability and reliability gain are also analytically derived. These analytical results provide basic design guidelines for wireless Distributed Consensus (WDC) usage in the C-CAS systems. The results show that WDC significantly improves overall system reliability with the increasing number of participating nodes.

R-PBFT: A secure and intelligent consensus algorithm for Internet of vehicles

Blockchain applications in the Internet of Vehicle (IoV) employ a secure and distributed consensus method, such as Practical Byzantine Fault Tolerance (PBFT) and Proof-of-Work (PoW), to reduce the load on the central server of IoV and the likelihood of single-node attacks. While traditional consensus algorithms based IoV improves consistency, efficiency, and eliminates single-node attacks, it has some limitations, including a delayed consensus process, restricted transaction frequency, and substantial block congestion. To address these limitations, we propose a fast and intelligent consensus mechanism called R-PBFT (Reputed PBFT). The R-PBFT improves the PBFT consensus process through the use of a reputation mechanism computed by logistic regression. We have built a testbed using the Raspberry Pi 4 and NVIDIA Jetson Nano platforms and experimented with the proposed scheme. The experiment result shows that the proposed R-PBFT outperforms state-of-the-art approaches by minimizing consensus delay by 50%, improving transaction frequency by 24% and throughput by 50%, reducing block congestion by 57%, and improves fairness by 15%. According to security analysis, R-PBFT is secure against Finney, Sybil, eclipse, routing, and impersonation attacks.

Reinforced practical Byzantine fault tolerance consensus protocol for cyber physical systems

Cyber–physical systems (CPS) are becoming an essential component of modern life. CPS services enable information to be exchanged between physical devices and virtual systems. The increasing malicious activities causing confidential data leakage and incorrect performance of devices are posing challenges for protection against cyber threats. Therefore, development of effective solutions that can protect both CPS data and data exchange networks are extremely urgent. This study makes some improvements on Practical Byzantine Fault Tolerance (PBFT), and provides a critical analysis of the feasibility of using blockchain technology to protect constrained CPS data. It also justifies the choice of the improved PBFT for implementation on such devices and simulates the main distributed ledger scenarios. The improved PBFT works as follows: first, the client broadcasts the signed transaction data to the entire network, rather than just the master node, followed by a hash value comparison verification process; second, select the master node based on the longest chain principle, and punish the malicious node via the “blacklist” mechanism; third, add the data synchronization and verification process, as well as dynamically entering and leaving nodes via state transitions. Ultimately, the PBFT commit phase is eliminated, resulting in a two-stage process. In comparison to the original PBFT protocol, the Reinforced Practical Byzantine Fault Tolerance (RPBFT) protocol may substantially enhance system throughput and minimize consensus communication time, thereby improving overall system efficiency while guaranteeing security.

Secure PBFT Consensus-Based Lightweight Blockchain for Healthcare Application

Recent advancement in IoT technology has boosted the healthcare domain with enormous usage of IoT devices to provide elevated services to patients with chronic disorders on a real-time basis by the incorporation of IoT sensors on patients’ bodies. However, providing services ensuring security and maintaining the privacy of patients is a challenging task. Blockchain technology promises security in a distributed environment but popular consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) require huge computational resources and energy by making the IoT environment inefficient. This paper introduces a secure Practical Byzantine Fault Tolerance (PBFT) consensus-based lightweight blockchain algorithm for healthcare applications. To strengthen the PBFT consensus, highly trusted nodes were allowed to participate in the consensus algorithm using the Eigen Trust model and Verifiable Random Function (VRF) to select a random primary node from a group of trusted consensus nodes. The proposed algorithm is tested in a simulated environment and evaluated against the traditional PBFT consensus algorithm considering throughput, latency, and fault tolerance.

A Parallel Consensus Mechanism Using PBFT Based on DAG-Lattice Structure in the Internet of Vehicles

The blockchain technology in the Internet of Vehicles (IoV) can be applied to solve security problems. Due to the high dynamics and resource constraints of the IoV, the traditional single-chain blockchain system is not suitable for the practical scenarios. In our previous work, we proposed a lightweight blockchain architecture based on the directed acyclic graph lattice (DAG-lattice) structure for the IoV. However, the current consensus algorithms are not suitable for the previous architecture mentioned above. Therefore, this article proposes a parallel consensus mechanism based on the DAG-lattice structure in the IoV using practical Byzantine fault tolerance (PBFT) as consensus algorithm. This mechanism solves the problem of low efficiency of PBFT caused by too many consensus nodes and the mobility of nodes by adopting the method of network sharding, and meanwhile to ensure that transactions can be reached on consensus parallelly. To avoid the selection of primary nodes from being predicted in advance, this article proposes a primary node selection method based on verifiable random function (VRF). Moreover, a method is proposed of selecting transactions based on weighted round robin (WRR) scheduling to motivate nodes for the purpose of maintaining a high reputation score. Finally, the performance of the proposed scheme is verified by experiments whose results show that the proposed consensus mechanism shows better performance than other comparable schemes in terms of the time added to the blockchain, transaction per second (TPS), consensus success rate, and the time of obtaining transaction. And the proposed mechanism is less dependent on roadside unit (RSU).

Sharding-Based Proof-of-Stake Blockchain Protocols: Key Components & Probabilistic Security Analysis

Blockchain technology has been gaining great interest from a variety of sectors including healthcare, supply chain, and cryptocurrencies. However, Blockchain suffers from a limited ability to scale (i.e., low throughput and high latency). Several solutions have been proposed to tackle this. In particular, sharding has proved to be one of the most promising solutions to Blockchain's scalability issue. Sharding can be divided into two major categories: (1) Sharding-based Proof-of-Work (PoW) Blockchain protocols, and (2) Sharding-based Proof-of-Stake (PoS) Blockchain protocols. The two categories achieve good performances (i.e., good throughput with a reasonable latency), but raise security issues. This article focuses on the second category. In this paper, we start by introducing the key components of sharding-based PoS Blockchain protocols. We then briefly introduce two consensus mechanisms, namely PoS and practical Byzantine Fault Tolerance (pBFT), and discuss their use and limitations in the context of sharding-based Blockchain protocols. Next, we provide a probabilistic model to analyze the security of these protocols. More specifically, we compute the probability of committing a faulty block and measure the security by computing the number of years to fail. We achieve a number of years to fail of approximately 4000 in a network of 4000 nodes, 10 shards, and a shard resiliency of 33%.

Blockchain‐based reliable image copyright protection

AbstractThe indiscriminate distribution of a large number of unlicensed images through the Internet seriously harms the benefits of image owners, which prompts the study of image copyright protection solutions. Existing blockchain‐free solutions are limited to using centralized servers to store copyright information, leaving data vulnerable to being lost or tampered with by external attacks. Although the blockchain‐based image copyright protection solutions are capable of addressing the above problem, improvements are needed in choosing a suitable blockchain platform and supporting integrated copyright life cycle management. To this end, this paper designs a blockchain‐based reliable image copyright protection system named BB‐RICP using Hyperledger Fabric. For one thing, the adoption of Fabric mitigates the limitations of other blockchain platforms represented by Ethereum in terms of efficiency, economy, and availability. For another, BB‐RICP successes in achieving integrated copyright lifecycle management. In addition, BB‐RICP achieves enhanced applicability performance by firstly introducing GM algorithms recommended by Chinese national standard and adapting the more consortium blockchain‐oriented practical byzantine fault tolerance algorithm. Moreover, the adoption of spread spectrum watermarking brings convenience to users. Finally, Kubernetes is used to assist in the simulation of BB‐RICP to verify that users can operate reliably in the blockchain network.

Dynamic Secure Access Control and Data Sharing Through Trusted Delegation and Revocation in a Blockchain-Enabled Cloud-IoT Environment

The Internet of Things (IoT) is vulnerable to leakage of private information during data sharing. To avoid this problem, access control and secure data sharing have been introduced in IoT; however, many challenges are faced because of centralized access control and single delegator selection. Additionally, blockchain is integrated into IoT to enhance the security of the environment. For that purpose, this research proposes dynamic secure access control using the blockchain (DSA-Block) model, which performs secure access control and data sharing. Initially, the IoT device attributes and user attributes are registered at a local domain authority (LDA) for generating private and public keys using the hyperelliptic curve cryptography (HECC) algorithm, which ensures the legitimacy of the users and devices. Then, the IoT devices send a request message to the edge nodes (ENs) via a gateway, which performs request filtration by validating the user’s authenticity. The filtered requests are sent to the edge server to perform access delegation using rock hyraxes swarm optimization (RHSO), which selects a set of delegator nodes. The access control decision is made by using the Trusted practical Byzantine fault tolerance (PBFT) consensus algorithm. The IoT data are stored in the cloud server for secure storage, in which the data are secured using a differential privacy mechanism. Finally, dual revocations, such as user attribute revocation and user revocation, are used to maintain security. The performance of DSA-Block is evaluated and the results demonstrate that the proposed DSA-Block model achieves superior performance compared to previous works.

Enhanced Multiset Consensus Protocol Based on PBFT for Logistics Information Traceability

In the recent years, the global logistics industry has greatly driven the development of the world economy. At the same time, a large amount of data information is generated. Due to the frequent occurrence of logistics information leakage and forgery, it is necessary to find solutions that can accurately trace logistics information and ensure the security and authenticity of logistics information. The birth of blockchain technology has transformed the logistics industry from quantitative change to qualitative change. The technical characteristics of blockchain technology, such as distributed storage ideas, decentralization, immutability, and complex encryption consensus algorithm, endow it with a wide range of application prospects in the logistics industry. This paper proposes an enhanced multiset consensus algorithm based on PBFT (practical Byzantine fault tolerance) for logistics information traceability and storage on the logistics blockchain. The application of the proposed multi-set consensus algorithm in the topology structure composed of multiple sets can improve the consensus efficiency of logistics information in the blockchain. We improve consensus capability and transaction speed, avoid redundant consensus message packets occupying a large bandwidth, and efficiently process logistics information generated at any time. We ensure the traceability of logistics information and achieve efficient and accurate traceability, and the efficiency and security of the proposed algorithm are analyzed. This paper aims to solve the problems of traceability, trustworthiness, and efficient processing of blockchain applications in logistics information to operate the logistics network efficiently. This paper compares the proposed algorithm with the PBFT-related expansion algorithm regarding bandwidth occupation, delay, and throughput. The results show that the MPBFT consensus algorithm significantly improves the efficiency of the logistics blockchain network.

EBMICQL: Improving Efficiency of Blockchain Miner Pools via Incremental and Continuous Q-Learning Framework

Blockchain mining pools assist in reducing computational load on individual miner nodes via distributing mining tasks. This distribution must be done in a non-redundant manner, so that each miner is able to calculate block hashes with optimum efficiency. To perform this task, a wide variety of mining optimization methods are proposed by researchers, and most of them distribute mining tasks via statistical request processing models. These models segregate mining requests into non-redundant sets, each of which will be processed by individual miners. But this division of requests follows a static procedure, and does not consider miner specific parameters for set creation, due to which overall efficiency of the underlying model is limited, which reduces its mining performance under real-time scenarios. To overcome this issue, an Incremental & Continuous Q-Learning Framework for generation of miner-specific task groups is proposed in this text. The model initially uses a Genetic Algorithm (GA) method to improve individual miner performance, and then applies Q-Learning to individual mining requests. The Reason for selecting GA model is that it assists in maintaining better speed-to-power (S2P) ratio by optimization of miner resources that are utilized during computations. While, the reason for selecting Q-Learning Model is that it is able to continuously identify miners performance, and create performance-based mining pools at a per-miner level. Due to application of Q-Learning, the model is able to assign capability specific mining tasks to individual miner nodes. Because of this capability-driven approach, the model is able to maximize efficiency of mining, while maintaining its QoS performance. The model was tested on different consensus methods including Practical Byzantine Fault Tolerance Algorithm (PBFT), Proof-of-Work (PoW), Proof-of-Stake (PoS), and Delegated PoS (DPoS), and its performance was evaluated in terms of mining delay, miner efficiency, number of redundant calculations per miner, and energy efficiency for mining nodes. It was observed that the proposed GA based Q-Learning Model was able to reduce mining delay by 4.9%, improve miners efficiency by 7.4%, reduce number of redundant computations by 3.5%, and reduce energy required for mining by 7.1% when compared with various state-of-the-art mining optimization techniques. Similar performance improvement was observed when the model was applied on different blockchain deployments, thus indicating better scalability and deployment capability for multiple application scenarios.

Block Chain for IOT Security Using Consensus Algorithms

The first distributed recordkeeping system with a built-in trust structure is the block chain. It creates a dependable architecture for decentralized control through information redundancy across multiple nodes. Based on this, this study suggests a minimal block chain-based IoT information exchange security framework. The framework uses a double-chain approach that combines the data block chain and the transaction block chain. Distributed storage and tamper-proof data are implemented in the data block chain, and the consensus process is improved using the improved practical Byzantine fault-tolerant (PBFT) mechanism. Data registration efficiency, resource and data transfers, and privacy protection are all enhanced by better partial blind signature-based algorithms in the transaction block chain. This article focuses on how well the consensus algorithms employed in a block chain system for the Internet of Things perform (IoT). Such systems' time requirements to accomplish. Consensus ought to be minimal. The three most popular consensus algorithms—modified proof of work, realistic byzantine fault tolerance, and binary consensus—are assessed under various conditions, including mote type, number of participating nodes, and radio propagation model. To enable an IoT node to switch between different consensus algorithms, a comprehensive solution is put forward. The Contiki IoT operating system simulations display strong performance (time to achieve consensus less than seconds)

Design of Proof-of-Stake PBFT Algorithm for IoT Environments

Blockchain ledgers are being increasingly used in Internet of Things (IoT) and Internet of Vehicles (IoV) applications. However, Proof of Work consensus is unsuitable in an IoV setting, which is why other paradigms need to be investigated. In this work we integrate Proof of Stake (PoS) consensus technique with multiple entry Practical Byzantine Fault Tolerance voting in a permissioned blockchain network. We introduce several PoS classes based on combination of initial stake and truthfulness of voting. We also describe a differentiated medium access approach similar to Enhanced Distribution Function (EDCA). Using a Semi Markov Process-based model, we derive the probability of reaching consensus and highlight the impact of the populations of individual stake/priority classes on achieving consensus. Our results show the impact of numbers of nodes from classes with different voting behavior on consensus probability. Results also show differentiation through the number of blocks linked per second, success probability in leadership application and delay in leader selection for node belonging to certain class. These values show how much revenue a node from given class can collect from its clients depending on initial stake and voting behavior.