Research on Security Consensus Algorithm Based on Blockchain

With the rapid development of Bitcoin, blockchain has also received more and more attention, and consensus algorithm is the key to the development of blockchain technology, which directly affects the security, scalability, and transaction processing speed of blockchain. This paper analyzes the popular consensus algorithm and its evolution. The representative consensus algorithm is analyzed in detail. The evaluation system of consensus algorithm is given from four aspects of security, decentralization, consistency, and scalability, hoping to provide a reference for the development and innovation of consensus algorithm.

With the rapid development of blockchain technology, consensus algorithms have become a significant research focus. Practical Byzantine Fault Tolerance (PBFT), as a widely used consensus mechanism in consortium blockchains, has undergone numerous enhancements in recent years. However, existing review studies primarily emphasize broad comparisons of different consensus algorithms and lack an in-depth exploration of PBFT optimization strategies. The lack of such a review makes it challenging for researchers and practitioners to identify the most effective optimizations for specific application scenarios. In this paper, we review the improvement schemes of PBFT from three key directions: communication complexity optimization, dynamic node management, and incentive mechanism integration. Specifically, we explore hierarchical networking, adaptive node selection, multi-leader view switching, and a hybrid consensus model incorporating staking and penalty mechanisms. Finally, this paper presents a comparative analysis of these optimization strategies, evaluates their applicability across various scenarios, and offers insights into future research directions for consensus algorithm design.

The blockchain technology revolution and the use of blockchains in various applications have resulted in many companies and programmers developing and customizing specific fit-for-purpose consensus algorithms. Security and performance are determined by the chosen consensus algorithm; hence, the reliability and security of these algorithms must be assured and tested, which requires an understanding of all the security assumptions that make such algorithms correct and byzantine fault-tolerant.This paper studies the "security ingredients" that enable a given consensus algorithm to achieve safety, liveness, and byzantine fault tolerance (BFT) in both permissioned and permissionless blockchain systems. The key contributions of this paper are the organization of these requirements and a new taxonomy that describes the requirements for security. The CAP Theorem is utilized to explain important tradeoffs between consistency and availability in consensus algorithm design, which are crucial depending on the specific application of a given algorithm. This topic has also been explored previously by De Angelis. However, this paper expands that prior explanation and dilemma of consistency vs. availability and then combines this with Buterin's Trilemma to complete the overall exposition of tradeoffs.

Cooperative control in multi-agent systems involves managing a group of agents that collaborate to accomplish a shared task. This approach has significant potential across various applications, including environmental monitoring, distributed aperture observing, traffic management, and more. A key technology employed in cooperative control is the consensus algorithm, which guides all agents to reach a common decision via communication. This dissertation aims to develop event-triggered consensus algorithms for linear multiagent systems (MASs) under general directed network. Under proposed algorithms, continuous information transmission and control input update are avoided so that unnecessary consumption of communication and computation resources can be reduced. In practical scenarios, agents may lack access to their complete state information as well as the overall network data. Building on the developed event-triggered consensus algorithm, an observer is designed to estimate each agent's state information, while an adaptive control law is utilized to infer the unknown aspects of the network. This allows the consensus algorithm to be entirely dependent on local state information, making it fully distributed. Using a developed extension method, these algorithms are first formulated for strongly connected networks and then adapted for general directed networks that contain a directed spanning tree.

Modern industry 4.0 applications are shifting towards decentralized automation of computing and cyber-physical systems (CPS), which necessitates building a robust, secure, and efficient system that performs complex interactions with other physical processes. To handle complex interactions in CPS, trust and consensus among various stakeholders is a prime concern. In a similar direction, consensus algorithms in blockchain have evolved over the years that focus on building smart, robust, and secure CPS. Thus, it is imperative to understand the key components, functional characteristics, and architecture of different consensus algorithms used in CPS. Many consensus algorithms exist in the literature with a specified set of functionalities, performance, and computing services. Motivated from these facts, in this survey, we present a comprehensive analysis of existing state-of-the-art consensus mechanisms and highlight their strength and weaknesses in decentralized CPS applications. In the first part, we present the scope of the proposed survey and identify gaps in the existing surveys. Secondly, we present the review method and objectives of the proposed survey based on research questions that address the gaps in existing studies. Then, we present a solution taxonomy of decentralized consensus mechanisms for various CPS applications. Then, open issues and challenges are also discussed in deploying various consensus mechanisms in the CPS with their merits and demerits. The proposed survey will act as a road-map for blockchain developers and researchers to evaluate and design future consensus mechanisms, which helps to build an efficient CPS for industry 4.0 stakeholders.

DTPBFT:A dynamic and highly trusted blockchain consensus algorithm for UAV swarm

Since the outbreak of the epidemic, people not only need to pay attention to their own safety and health, but also need insurance services to protect themselves. However, there are some problems in the traditional insurance system. First, the information of clients is incomplete or untrue. Second, privacy is compromised. Third, transaction information is tampered with. These problems lead to various insurance disputes. Therefore, this paper develops an insurance system based on blockchain by using the characteristics of decentralization, transparency, and immutability. The construction of the system is divided into three steps. First, insurance contracts are published on the Merkel tree. Next, RSA encryption technology is used to protect clients' information security. Last, SHA256 secure hash algorithm and consensus mechanism are used to resist the external attack of the blockchain. On this basis, this paper designs and develops a safe insurance system. Also, it studies the performance of insurance systems and the consensus mechanism of blockchain. The former compares the differences between the traditional insurance system and the blockchain insurance system in each performance index during operation. The result shows that some performance indices of blockchain insurance system are lower than those of traditional insurance system. However, because of its higher security than traditional insurance system, blockchain technology is selected as the core technology of this system. Also, two consensus algorithms, PoW and PBFT, compares with each other in blockchain technology. The experimental results show that the PoW consensus algorithm is more suitable for blockchain insurance system.

DC Microgrid attains popularity in integrating renewable energy sources and batteries. It also has the potential to achieve higher efficiency than ac power grid with optimized power flow. In this paper, a general dc microgrid is modeled based on a cluster of general dc nodes, which includes constant power renewables generation, droop-controlled voltage source and different kinds of load. Then the dc power flow is solved for optimization. A voltage restoration method based on consensus algorithm is used to restore the voltage deviation from droop characteristic. An enhanced current regulator is adopted to guarantee the accurate load sharing even under the influence of sensor drift and line resistance. A tie line power flow control method is proposed to regulate the tie line power directly and increase the system efficiency at light load condition. All the considered methods only need the local information and the information from its nearest neighbor thus the system expendability is guaranteed. Simulation and experiment results are provided to validate the proposed methods.

Continuous-time double integrator consensus algorithms improved by an appropriate sampling

A large number of wind turbine generators in the large-scale offshore wind farm system poses a challenge to the wind farm control system due to the computational burden in the central control methods or the complexity of the communication network in the decentralized control strategies. A hybrid control method based on the distributed consensus control and the central model predictive control is proposed in this study to overcome the problem. Typically, the wind turbine generators in the large-scale offshore wind farm system are clustered into several groups. The consensus-based distributed reactive power coordination control is proposed to each cluster and the centralized predictive voltage control is used to manage the total reactive powers of all clusters and regulate the voltage at the point of common coupling. The gradient-descent algorithm for the optimal design of the consensus-based cluster control is presented firstly. Based on the convergence property of the consensus control, the equivalent model of the total reactive power response of each cluster is identified, which is used for the design of the centralized predictive voltage control. Eigenvalue analysis of the proposed predictive control strategy is carried out to verify the stability of the distributed and predictive control systems. The robustness of the proposed predictive controller is evaluated in the conditions of significant model errors due to the communication delay in each cluster. A comparison study with the full distributed control based on consensus algorithm is presented to demonstrate the effectiveness of the proposed control method. The feasibility of the proposed predictive controller is evaluated by the control-hardware-in-the-loop simulation using OPAL-RT Technologies. An additional comparison study in term of computation time with the central control method is also carried out. Real-time simulation results show the superior performance of the proposed hybrid method compared to the full distributed consensus controller or the central control strategies.

The article contains an analytical review of developments in database technologies, made on the basis of reports prepared by the results of eight meetings of database specialists held throughout 1988–2013. Objects of the analysis are most interesting predictions given in the reports: their realism, accuracy, pragmatism or, vice versa, utopianism or opportunism. The article consists of two parts. Part 1 is devoted to analysis and evaluation of predictions made in the reports of the four earlier meetings held in 1988, 1990, 1995, and 1996. These predictions are about creation, development and uses of decision support systems, database appliances, graphic processing units, operating systems, interface for structured query language, database applications, information distribution, universal database management systems, query optimization criteria, intellectual analysis of database within database management systems. A detailed description of research themes in the field of databases, which got the priority status in that time, is given: recording and computation of data, security and confidentiality of data, replication and harmonization of data, structuring of data, intellectual analysis of data, data warehouses. Part 2 is devoted to an analytical review of the predictions contained in the reports on the meetings held in 1998, 2003, 2008, and 2013. The predictions are about self-adjustment of database systems, rethinking of the traditional database architecture as a result of new hardware capabilities. They make special emphasis on the feasibility of manipulations with structured and unstructured data within DSS architecture, support of Big Data technology, with outlining the themes of research aimed at implementation of its potential.

Swarm robotics is an emerging field capable of accomplishing complex tasks through collective behaviour. However, it continues to face persistent challenges in secure communication, decentralized decision-making, and scalability. To operate effectively in resource-constrained environments, swarm networks require a decentralized mechanism that is secure, fast, and efficient. Although many studies have explored the use of blockchain technology for swarm robotics, existing blockchain consensus algorithms such as Proof of Work (PoW), Proof of Stake (PoS), and their variants remain unsuitable due to high computational complexity and risk of stake centralization. To address these challenges, we introduce the blockchain-based Rotational Leadership Role (RLR) consensus algorithm, a voting-based consensus re-engineered from the Raft approach, together with Decentralized Task Authorization and Validation (DeTAV), a token-based mechanism for context-aware task validation. This design ensures efficiency, security, and scalability in swarm robotics and drone systems. RLR is lightweight and well suited to operate within the limited computing resources of small robots or aerial drones. To validate its performance, a custom-built robotic simulator was developed as part of this research. Experiments conducted with up to 70 concurrent robots demonstrated that RLR consumed under 90 MB Random Access Memory (RAM) and 12% Central Processing Unit (CPU), whereas PoW required 460 MB RAM and 27% CPU with a minimum difficulty level of 21, reflecting an 80% reduction in memory usage and a 55% reduction in CPU consumption. Scalability tests with 4 to 70 robots further revealed RLR’s scalability with an average of 78% higher throughput, 47% lower election latency, and 34% lower consensus latency. Additionally, under the simulated attack scenarios and assuming uncompromised cryptographic keys, DeTAV’s context-based validation consistently achieved 100% success in detecting and isolating Byzantine nodes, while reducing Quality of Detection (QoD) time by 67%. Collectively, these results confirm that RLR with DeTAV effectively meets the efficiency, security, and scalability requirements of swarm robotic and drone networks.

In recent years, with the continuous development and progress of information technology, the information system has had a huge impact on people's daily work and life, and has become an irreplaceable factor in our work and life. With the increasing number of applications of information technology, the information industry revolution is sweeping the world. Almost all industries, including the power industry, have begun to pay attention to the construction and innovation of information systems, and building a "modern supply chain" has become China's new economic development direction. The main purpose of this paper is to conduct research on the security risk monitoring of power supply chain (PSC) blockchain based on fuzzy neural network (FNN). This paper takes the theory of supply chain and the application of information system in an electric power enterprise as the starting point, and analyzes and studies the application of information system in the supply chain of an electric power enterprise. Using the concepts and theories of information system and SCM, the application of the information system of a power enterprise in its supply chain is analyzed and studied in detail. Experiments show that in the matching process, smart contracts play an important role according to different situations. Once the energy matching is successful, both parties will complete the energy transaction according to the content of the smart contract, and the entire EBN-IESCOM can be solved using blockchain technologies such as consensus algorithms and smart contracts..

Description of the problem: Despite long-term commitment to decentralization in India, progress towards a decentralized form of governance has been slow. In Karnataka, despite state compliance with decentralised governance legislation from the mid-1980s, local bodies continue to suffer from inadequate power and resources. Under the National Rural Health Mission (NRHM), decentralization plays a role in monitoring service access and quality. However, after almost a decade of organized decentralisation in the health sector, its impact is still not clear, nor its ability to enhance individuals/communities participation and ability to fulfil their health needs. Operational Definition : For the purpose of this research, we define decentralisation as a process which involves shifting of power and responsibilities between tiers of government by way of various fiscal, political, and administrative instruments. Rationale: Regardless of these arguments for and against decentralization, there is little evidence that shows the effects of decentralisation on health service delivery and changes in health indicators. There are few studies that have tried to assess the impact of decentralization on the provision of health care services and health outcomes and there is a lack of an analytical framework to empirically analyse its impact. As a result, there is limited empirical evidence on the impact of decentralization on improving delivery of health care services and health outcomes worldwide. Research Questions: The main questions we analyse through this study are: Does the degree of decentralisation under the NRHM correlate strongly with perceived decision space of Health Department officials and PRI members at the District level and below? Does the capacity of functionaries at different levels of the health system correlate with perceived decision space? Does greater perceived decision space by any given functionary/official lead to better health outcomes? Conceptual Framework : For the research purpose, we use Bossert’s analytical frame work. This framework outlines the concept of “Decision Space”, by studying the range of choice that different actors in the health system perceive as being available to them along a series of functional dimensions. Decentralization is expected to enhance service delivery of public services, as well as have a positive impact on both the performance and health outcomes in various country settings. A successful model of decentralization is meant to establish the broad framework for decentralization/devolution, leaving the detailed planning, operationalization and monitoring of the process to the lower levels of administration. The Alma Ata Declaration on Health for All acknowledges the role of decentralisation in public service delivery. Within the framework of decentralization, officials operate within an actual or perceived area of autonomy which is characterized as their decision space. The assumption is that within the boundaries of this decision space, officials are able to make innovative choices that promote their/the systems efficiency and effectiveness, and thereby enhance the achievement of measurable health outcomes. Methodology: The study builds on an initial pilot study in Tumkur district and extends it to an additional 6 districts of Karnataka, in a combination of developed and backward districts based on the Nanjundappa Committee report. The study includes both qualitative and quantitative data generated from questionnaires, interviews and focus group discussions at the district, taluk and panchayats levels. For the quantitative analysis, we designed a decision space questionnaire administered to a range of technocrats, bureaucrats and people’s representatives at the district level and below. The questions relate to the respondents’ perceptions of power at their disposal. Qualitative data will include interviews with the above-mentioned officials. Data pertaining to health outcome indicators taken from DLHS-3 and state NRHM program implementation plans are then analysed in relation to the perceived decision-space. Findings and Recommendations: The study demonstrates the relationship between perceived decision space and the effectiveness of the health system; and also provides insights into the impact of decentralization in diverse settings. The pilot study showed that: Decision space overall is limited among all officials at the district level; and the limitation is highest in matters relating to human resources, planning and budgeting. Program Officers appeared to have greater decision space, and greater control within the specific boundaries of their programs. People’s representatives have little influence over decisions made by the Health Department; however, they can contribute with their own funds to specific activities such as providing additional drugs or civil works. The government needs to spell out in greater detail the exact activities which can be devolved to lower levels of administration; and provide the financial and operational autonomy to bring about genuine empowerment at those levels. Officials need to be trained to be able to carry out the responsibilities allocated to them and to understand better what they can and cannot do under the framework of decentralized decision making.

With the development of power grid technology, the coordinated development of multiple types of source, network, load and storage is the future development trend. Advanced technologies based on blockchain and edge computing can efficiently utilize the advantages of energy blockchain and solve problems such as data security and flexible user transactions. To this end, this article formulates an important business application scenario of blockchain in the source network load storage, and proposes its design plan. At the same time, this article combines typical actual cases to calculate and analyze the relationship between the degree of decentralization and the operating efficiency of the microgrid. On this basis, this paper calculates the operating costs under different conditions, and finally puts forward the best operating strategy. The design scheme proposed in this paper can provide a new calculation reference for realizing the economic, high-efficiency and safe processing of a large amount of power transaction information.