Consensus Algorithm Analysis in Blockchain: PoW and Raft

This study applies reinforcement learning (RL) from the AI machine learning field to derive an optimal Bitcoin-like blockchain mining strategy. A salient feature of the RL learning framework is that an optimal (or near-optimal) strategy can be obtained without knowing the details of the blockchain network model. Previously, the most profitable mining strategy was believed to be honest mining encoded in the default blockchain protocol. It was shown later that it is possible to gain more mining rewards by deviating from honest mining. In particular, the mining problem can be formulated as a Markov Decision Process (MDP) which can be solved to give the optimal mining strategy. However, solving the mining MDP requires knowing the values of various parameters that characterize the blockchain network model. In real blockchain networks, these parameter values are not easy to obtain and may change over time. This hinders the use of the MDP model-based solution. In this study, we employ RL to dynamically learn a mining strategy with performance approaching that of the optimal mining strategy. Since the mining MDP problem has a nonlinear objective function (rather than linear functions of standard MDP problems), we design a new multidimensional RL algorithm to solve the problem. Experimental results indicate that, without knowing the parameter values of the mining MDP model, our multidimensional RL mining algorithm can still achieve optimal performance over time-varying blockchain networks.

The article investigates the process of block formation in blockchain networks and the impact of node network architecture and consensus algorithms on their scalability and performance. Analysis of blockchain system scalability is important due to problems that arise when network load increases, particularly the increase in the number of block forks and transaction confirmation times. The research focuses on studying the impact of network delays and the choice of consensus algorithm on the performance and scalability of blockchain networks. The main attention is devoted to mathematical models that describe block formation, as well as the analysis of factors affecting transaction processing speed and throughput. The primary consensus algorithms, such as Proof of Work (PoW) and Proof of Stake (PoS), are considered, and their impact on scalability in implementations based on the Ethereum Virtual Machine (EVM) and Bitcoin is compared. Experimental studies using Geth and Amazon cloud services revealed that the application of the Proof of Stake (PoS) consensus algorithm increases network performance by reducing the complexity of the block formation process in blockchain networks by 99% and accelerates consensus achievement by 70% compared to Proof of Work (PoW). It was also established that increasing the number of nodes from 5 to 50 reduces the network's throughput by almost 10%, and the average confirmation time doubles. The obtained results are aimed at solving the scalability issue by reducing transaction confirmation times for the implementation of decentralized technologies in the Internet of Things (IoT) sphere, where processing speed and storage of large volumes of data are critically important. Keywords: blockchain, block formation, consensus algorithms, decentralized technologies, Ethereum Virtual Machine (EVM), Internet of Things (IoT), mathematical modeling, network delays, scalability.

We study state aggregation for Markov decision processes (MDPs) with long-run average-cost optimality criterion in this paper. The aggregation is based on a definition of an (/spl epsiv//sub p/, /spl epsiv//sub f/)-lumpable partition of the state space, where the difference between the control effect of any control action on any two states belonging to the same subset in the partition is bounded by /spl epsiv//sub p/ for the state-transition effect and /spl epsiv//sub f/ for the cost effect. The states in the same partition subset are treated into one meta-state to obtain an aggregated Markov chain. We then construct an aggregated MDP with average cost on the aggregated Markov chain. We develop an algorithm to find the solution to this aggregated MDP problem and show its performance is within some o(/spl epsiv//sub p/, /spl epsiv//sub f/) neighborhood of the optimal solution to the original MDP problem. In real applications, the (/spl epsiv//sub p/, /spl epsiv//sub f/)-lumpable partition is usually obtained empirically. However, we also study the problem of looking for the coarsest (/spl epsiv//sub p/, /spl epsiv//sub f/)-lumpable partition, i.e., the partition with minimum number of subsets, given /spl epsiv//sub p/ and /spl epsiv//sub f/. We prove that this partitioning problem is in the time complexity class of P-hard, which is not easier than the original MDP problem in the class of P-complete.

Aiming at the performance bottleneck problem and insufficient scalability caused by consensus algorithm in supply chain financing application scenarios, this paper proposes a Multi-Raft consensus algorithm for improving the Raft consensus algorithm. In the Multi-Raft consensus algorithm, we introduce the contractor election algorithm. Contractor nodes are selected by the KNN algorithm in machine learning. The optimized Multi-Raft consensus algorithm is applied to the Easy-Visible supply chain financing platform for testing. By analyzing the experimental results, it can be seen that the optimized Multi-Raft consensus algorithm has significant improvements in throughput, delay and scalability compared with the original Raft consensus algorithm. The research in this paper solves the problems of performance bottleneck and low scalability of the consensus algorithm of the alliance chain in practical applications. A solution is proposed for the large-scale implementation of the enterprise-level alliance chain. It has certain engineering value and application value.

The proof-of-work (PoW) algorithm has been initially used in Bitcoin and is now one of the mainstream consensus algorithms to create immutable ledgers of transactions. However, it is still not very well understood, and as such, its entire strength remains undervalued. While some researchers classify it as a Nakamoto consensus algorithm, some other researchers do not even consider it as a consensus algorithm. In this article, the objective is to shed light on classifying PoW. To this end, we make a theoretical analysis from a coordination perspective, and then we conclude that PoW is a stigmergic consensus algorithm where the trace left by an action in the blockchain through indirect coordination of agents stimulates a subsequent action and eventually creates a single chain of blocks. In other words, PoW is a form of stigmergic coordination toward emergent behavior of a blockchain system. Based on this identification, we further analyze the fundamental properties of PoW. Finally, we reengineer PoW by improving its missing stigmergic mechanisms, and we provide a discussion.

Cryptocurrencies have seen a massive surge in popularity and behind these new virtual currencies is an innovative technology called the blockchain: a distributed digital ledger in which cryptocurrency transactions are recorded after having been verified. The transactions within a ledger are verified by multiple clients or “validators,” within the cryptocurrency's peer-to-peer network using one of many varied consensus algorithms for resolving the problem of reliability in a network involving multiple unreliable nodes. The most widely used consensus algorithms are the Proof of Work (PoW) algorithm and the Proof of Stake (PoS) algorithm; however, there are also other consensus algorithms which utilize alternative implementations of PoW and PoS, as well as other hybrid implementations and some altogether new consensus strategies. In this paper, we perform a comparative analysis of typical consensus algorithms and some of their contemporaries that are currently in use in modern blockchains. Our analysis focuses on the algorithmic steps taken by each consensus algorithm, the scalability of the algorithm, the method the algorithm rewards validators for their time spent verifying blocks, and the security risks present within the algorithm. Finally, we present our conclusion and some possible future trends for consensus algorithms used in blockchains.

Enterprises have focused much of their attention on consortium blockchains, in which multiple authorized organizations participate to form a consortium, in contrast to public blockchains, which consist of unspecified participants. Since a system using a blockchain is based on participants providing/using resources such as nodes to each other, a mechanism to motivate participants to provide resources is important. Typically, a public blockchain realizes an incentive mechanism for providing nodes by unspecified participants through mining rewards and transaction fees associated with a consensus algorithm such as PoW on the platform layer. On the other hand, a consortium blockchain usually does not have an incentive mechanism in the platform itself. In order to maintain and operate a consortium, it is essential that participating organizations provide resources or pay the costs of providing resources. However, because participating organizations use different percentages of the resources, a uniform fee could create inequalities or unfair situations among organizations. Therefore, it is necessary to manage billing to remove the gap between the costs borne and the actual usage or/and the unfairness among participants in the consortium. This research aims to realize a billing management method for consortium blockchain-based systems. We propose a smart contract-based service billing management mechanism named “BillingOpsSC” to ensure cross-organizational transparency for billing calculation and management. Furthermore, to ensure fairness among participants, we design a billing calculation model based on metering of the “contribution” by each organization such as providing resources, and the system “usage” by each organization, in the consortium. We implement a prototype of the proposed method including the billing management mechanism and calculation model for Hyperledger Fabric, which is one of the major consortium blockchains, and evaluate the method using the prototype. The results show that our proposed method is effective in ensuring transparency and fairness in billing management among multiple organizations, and in terms of performance is practical enough to be used in making monthly billing calculations.

Consensus algorithms are essential for achieving agreement among nodes in blockchain systems. However, traditional consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) can be resource-intensive and unsuitable for lightweight private blockchain applications. This paper proposes using the RSA (Rivest–Shamir–Adleman) encryption algorithm as a consensus algorithm for a lightweight private blockchain in the context of a college placement system. RSA offers several advantages over traditional consensus algorithms, including simplicity, efficiency, and security. Moreover, RSA can be implemented on resource-constrained nodes, making it a promising solution for lightweight blockchain applications. The resource constrained nodes are students, academic department, training and placement cell department, and placement cell coordinator. The company acts as a client. The movement of the student’s data to companies is recorded as transactions on the distributed ledger or blockchain, allowing the student to track its progress.

Recently, studies on early-exit mechanisms have emerged to reduce the computational cost during the inference process of deep learning models. However, most existing early-exit architectures simply determine early exiting based only on a target confidence level in the prediction, without any consideration of the computational cost. Such an early-exit criterion fails to balance accuracy and cost, making it difficult to use in various environments. To address this problem, we propose a novel, cost-effective early-exit architecture in which an early-exit criterion is designed based on the Markov decision process (MDP). Since the early-exit decisions within an early-exit model are sequential, we model them as an MDP problem to maximize accuracy as much as possible while minimizing the computational cost. Then, we develop a cost-effective early-exit algorithm using reinforcement learning that solves the MDP problem. For each input sample, the algorithm dynamically makes early-exit decisions considering the relative importance of accuracy and computational cost in a given environment, thereby balancing the trade-off between accuracy and cost regardless of the environment. Consequently, it can be used in various environments, even in a resource-constrained environment. Through extensive experiments, we demonstrate that our proposed architecture can effectively balance the trade-off in different environments, while the existing architectures fail to do so since they focus only on reducing their cost while preventing the degradation of accuracy.

In the white book of Bitcion, Satoshi Nakamoto described a bitcoin system that can realize point-to-point online payment without a third-party organization. After supporting this magical application scenario and subverting the traditional centralized system, the blockchain technology has attracted worldwide attention, triggered a research upsurge of blockchain consensus algorithm, and produced a large number of innovative applications. Although various consensus algorithms continue to evolve with the iteration of blockchain products and applications, Proof of Work (POW) and Proof of Skake (POS) algorithms are still the core of consensus algorithms. This paper discussestwo algorithms of POW and POS in blockchain consensus mechanism, and analyzes the advantages and the existing problems of the two consensus mechanisms. Since consensus mechanism is the main focus of blockchain technology and has many influencing factors, this paper discusses the current problems and some improved ideas, and selectes some typical algorithms for a more systematic introduction. In addition, some important issues related to safety and performance are also discussed. This paper provides the researchers a great reference on blockchain consensus mechanism.

The consensus algorithm has been popular in current distributed systems as it is more effective in solving server unreliability. It ensures a group of servers can form a coordinated system, and the entire system continues to work when a part of the service point fails. Raft is a well-known and widely used distributed consensus algorithm, but as it has a built-in purpose of comprehensibility, it is always compromised in terms of performance as a trade-off. In this paper, we mainly aim to improve the traditional Raft consensus algorithm’s performance problem, especially in high concurrency scenarios. We introduce a pre-proposal stage on top of the algorithm to achieve efficiency optimization through batch asynchronous log replicated and disk flushing. The experiment proved that the improved Raft could increase the system throughput by 2–3.6 times, and the processing efficiency for parallel requests can be increased by 20% or more.

Diverse technologies, such as machine learning and big data, have been driving the prosperity of the Internet of Things (IoT) and the ubiquitous proliferation of IoT devices. Consequently, it is natural that IoT becomes the driving force to meet the increasing demand for frictionless transactions. To secure transactions in IoT, blockchain is widely deployed since it can remove the necessity of a trusted central authority. However, the mainstream blockchain-based IoT payment platforms, dominated by Proof-of-Work (PoW) and Proof-of-Stake (PoS) consensus algorithms, face several major security and scalability challenges that result in system failures and financial loss. Among the three leading attacks in this scenario, double-spend attacks and long-range attacks threaten the tokens of blockchain users, while eclipse attacks target Denial of Service. To defeat these attacks, a novel bidirectional-linked blockchain (BLB) using chameleon hash functions is proposed, where bidirectional pointers are constructed between blocks. Furthermore, a new committee members auction (CMA) consensus algorithm is designed to improve the security and attack resistance of BLB while guaranteeing high scalability. In CMA, distributed blockchain nodes elect committee members through a verifiable random function. The smart contract uses Shamir's secret-sharing scheme to distribute the trapdoor keys to committee members. To better investigate BLB's resistance against double-spend attacks, an improved Nakamoto's attack analysis is presented. In addition, a modified entropy metric is devised to measure eclipse attack resistance across different consensus algorithms. Extensive evaluation results show the superior resistance against attacks and demonstrate high scalability of BLB compared with current leading paradigms based on PoS and PoW.

Healthcare Blockchains (HBC) are grooming nowadays due to the requirements of flexible Electronic Health Records (EHR) management, privacy needs, and controlled medical data access. Blockchain technology very much suits these requirements and support in various healthcare data access control methods. More focus on improved block generation time gives the expected blockchain performance. Block generation time can be significantly improved by the consensus algorithms used by the system. Traditional consensus algorithm of Proof of Work (PoW) and Proof of Stake (PoS) require heavy computational resources and hence by computational overheads. The proposed system introduces a new privacy-preserving HBC consensus protocol as a consequence of member attribute values and significantly reduced computational resources. The new attribute-based consensus algorithm for HBC called Proof of Policy (PoP) is constructed using Attribute-Based Ring Signature (ABRS). This signature agrees on the stake of attribute-based ring membership and can be considered as an extension of Proof of Stake (PoS). It is also found that the proposed PoP consensus algorithm requires less computational resources than popular PoW and PoS.

The arrival of the Proof of Stake (POS) consensus algorithm has solved the problem of energy waste caused by Proof of Work (POW) through replacing POW’s wasteful computing power with proof of possession of a certain amount of locked token called “Stake”. The weight of the latter will allow its holder to be more likely to be selected as “Leader” and earn a corresponding reward. However, the mechanism adopted by POW, the POS (and its derivatives) promotes the mining monopoly by the most powerful or the wealthiest members of the network without any other tangible criterion proving that these participants actively contribute to the security of the Blockchain network and respect the security recommendations (application of urgent updates for example) issued by the development team of said Blockchain.In this paper, we propose a new consensus algorithm called “Proof of Conformity -PoC-” favoring the node security aspect and offering additional reliability to the Blockchain. Proof of Conformity improvement involves the introduction of a new impact factor in the node weight calculation named “Node Security Metric” (NSM).NSM is primarily based on the Common Vulnerability Scoring System (CVSS). Furthermore, NSM computation mainly relies on the re-calculation of the weight of each network node based on the stability and security of their software and hardware environment. Our new approach will strengthen the node security index and encourage miners with up-to-date environments. Moreover, compliant, proactive and vigilant nodes will increase their chances of being selected as “Leader” and earning rewards.PoC is theoretically evaluated through simulation scenarios and the result obtained shows that our approach ensures that participating nodes deemed secure are more likely to be designated as “Leader” based on their conformity rates reflected by their NSM score.KeywordsBlockchainConsensus algorithmCVSSDistributed systemSecurityProtocolsDecentralised system

Halal Supply Chain Management requires an assurance that the entire process of procurement, distribution, handling, and processing materials, spare parts, livestock, work-in-process, or finished inventory to be well documented and performed fit to the Halal and Toyyib. Blockchain technology is one alternative solution that can improve Halal Supply Chain as it can integrate technology for information exchange during the tracking and tracing process in operating and monitoring performance. This technology could improve trust, transparency, and information disclosure between supply chain participants since it could act as a distributed ledger and entitle all transactions to be completely open, yet confidential, immutable, and secured. This study uses a Blockchain Network with three channels and uses raft consensus algorithm in designing web interfaces and testing their capabilities. From the web interface, there were no failures in the validity test during the invoke test and the query test. In addition, the web interface was also successfully tested to thwart the formation of a block in case of data input errors from the user. The server can also do the process as a provider of information and validator for the web interface. From the results of simulations conducted on the Blockchain Network that was made, Blockchain’s transaction speed is fast and all the transaction is successfully transferred to other peers. Thus, Permissioned Blockchain is useful for Halal Supply Chain not just because it can secure transactions from some of the halal issues, but the transaction speed and rate to transfer data are very effective.