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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Pawar, Manjula K Hiregowdar, Harshitha S Joshi, Sukruti Kle Technological University Department of Computer Engineering Karnataka Hubli India

ISBN: (纸本)9798350308846

This research paper presents the design and implementation of a land registry system using multiple nodes with Geth, a command-line interface for running Ethereum nodes. The system is designed to address the issues of security and efficiency in the current land registration system. The system uses a distributed database with multiple nodes to store land records, providing redundancy and fault tolerance. The use of a distributed database also ensures that no single point of failure exists, improving the system's reliability. To ensure that the land records are impenetrable and cannot be changed without permission, the system makes use of the Ethereum blockchain. A consensus mechanism is used to implement the blockchain, ensuring that every node on the network concurs with the database's current state. The use of a consensus algorithm ensures that the system is secure and resilient to attacks. To automate the transfer of land ownership, the system also includes a smart contract framework. The smart contract system ensures that all parties involved in a land transaction agree on the terms of the transaction before it is executed. This reduces the possibility of land transaction conflicts. The system was developed using Geth, a commandline interface for managing Ethereum nodes. The system was tested using a simulated network of nodes and was found to be reliable and efficient. The system showed high throughput and low latency, which qualified it for usage in a production setting. © 2023 IEEE.

关键词： consensus algorithm Distributed Database Ethereum Blockchain Geth Land Registry System Smart Contract

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A Spectral algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm 37

A Spectral Algorithm for List-Decodable Covariance Estimatio...

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Diakonikolas, Ilias Kane, Daniel M. Lee, Jasper C.H. Pensia, Ankit Pittas, Thanasis University of Wisconsin-Madison United States University of California San Diego United States IBM Research United States

We study the problem of list-decodable Gaussian covariance estimation. Given a multiset T of n points in d such that an unknown α © 2023 Neural information processing systems foundation. All rights reserved.

ISBN: (纸本)9781713899921

关键词： consensus algorithm

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Enhancing Stability and Assessing Uncertainty in Community Detection through a consensus-based Approach

arXiv

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arXiv 2024年

作者： Morea, Fabio De Stefano, Domenico Area Science Park Padriciano Trieste99 Italy University of Trieste Piazzale Europa 1 Trieste Italy

Complex data in social and natural sciences find effective representation through networks, wherein quantitative and categorical information can be associated with nodes and connecting edges. The internal structure of networks can be explored using unsupervised machine learning methods known as community detection algorithms. The process of community detection is inherently subject to uncertainty as algorithms utilize heuristic approaches and randomised procedures to explore vast solution spaces, resulting in non-deterministic outcomes and variability in detected communities across multiple runs. Moreover, many algorithms are not designed to identify outliers and may fail to take into account that a network is an unordered mathematical entity. The main aim of our work is to address these issues through a consensus-based approach by introducing a new framework called consensus Community Detection (CCD). Our method can be applied to different community detection algorithms, allowing the quantification of uncertainty for the whole network as well as for each node, and providing three strategies for dealing with outliers: incorporate, highlight, or group. The effectiveness of our approach is evaluated on artificial benchmark networks. © 2024, CC BY.

关键词： consensus algorithm

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A Geometric Approach to Resilient Distributed consensus Accounting for State Imprecision and Adversarial Agents

A Geometric Approach to Resilient Distributed Consensus Acco...

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American Control Conference (ACC)

作者： Christopher A. Lee Waseem Abbas Electrical Engineering Department University of Texas at Dallas Richardson TX USA Systems Engineering Department University of Texas at Dallas Richardson TX USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper presents a novel approach for resilient distributed consensus in multiagent networks when dealing with adversarial agents and imprecision in states observed by normal agents. Traditional resilient distributed consensus algorithms often presume that agents have exact knowledge of their neighbors' states, which is unrealistic in practical scenarios. We show that such methods are inadequate when agents only have access to imprecise states of their neighbors. To overcome this challenge, we adapt a geometric approach and model an agent's state by an ‘imprecision region’ rather than a point in $\mathbb{R}^{d}$ . From a given set of imprecision regions, we first present an efficient way to compute a region that is guaranteed to lie in the convex hull of true, albeit unknown, states of agents. We call this region the invariant hull of imprecision regions and provide its geometric characterization. Next, we use these invariant hulls to identify a safe point for each normal agent. The safe point of an agent lies within the convex hull of its normal neighbors' states and hence is used by the agent to update it's state. This leads to the aggregation of normal agents' states to safe points inside the convex hull of their initial states, or an approximation of consensus. We also illustrate our results through simulations.

关键词： Adaptation models Uncertainty Computational modeling consensus algorithm Resilience

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A novel phase-only pattern nulling algorithm

A novel phase-only pattern nulling algorithm

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IET International Radar Conference 2023, IRC 2023

作者： Lu, Chengjun Meng, Ziqiang Shan, Jiaolong AVIC Leihua Electronic Technology Institute Wuxi China

ISBN: (纸本)9781839539954

In order to obtain low probability of intercept, it is required to form nulling in the transmit pattern for the phased radar. To solve the problem, a novel phase-only pattern nulling algorithm is proposed in this paper. First, dummy interferences are introduced according to the nulling angles, and the interference covariance matrix is calculated;then the mathematical model for forming nulling is established by minimizing the array output power;last, the phase-only weight can be obtained by the single coordinate algorithm. The experimental results demonstrate the correctness and effectiveness of the proposed approach. © The Institution of Engineering & Technology 2023.

关键词： consensus algorithm

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consensus-based algorithms for stochastic optimization problems

arXiv

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arXiv 2024年

作者： Bonandin, Sabrina Herty, Michael RWTH Aachen University Germany

We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective function by consensus-based particle optimization methods on the search space are developed. The resulting methods are mathematically analyzed using a mean-field approximation, and their connection is established. Several numerical experiments show the validity of the proposed algorithms and investigate their rates of *** Codes 82B40, 65K10, 60K35 Copyright © 2024, The Authors. All rights reserved.

关键词： consensus algorithm

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Addressing Blockchain Efficiency: A Study on Super Node-Based consensus Mechanisms

Addressing Blockchain Efficiency: A Study on Super Node-Base...

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Advanced Computing and Emerging Technologies (ACET), International Conference on

作者： Kamal Kant Sarvesh Pandey Udai Shanker Department of Computer Science & Engineering M. M. M. University of Technology Gorakhpur India Computer Science – MMV Banaras Hindu University Varanasi India

ISBN: (数字)9798350367720

ISBN: (纸本)9798350367737

The success of applying blockchain technology for transaction processing is based on a consensus mechanism to be utilized. The new solutions for the same are being reported and claiming to fix or overcome it. However, the reported consensus protocols are not capable enough to serve the purpose adequately because the majority of widely used blockchain platforms purposefully exclude metrics like delay and throughput, which are essential for the efficiency of consensus protocols. Therefore, this paper discusses blockchain fundamentals, consensus mechanisms, their variants, and our super node concept is discussed, and we perform extensive experiments and our analysis preliminary results indicate that as the number of nodes increases, the throughput increases rapidly.

关键词： Measurement Scalability consensus algorithm Throughput consensus protocol Delays Complexity theory Security

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A Novel Federated Learning System with Privacy Protection and Blockchain consensus Incentive Mechanisms in Cloud-Edge Collaboration Scenarios

A Novel Federated Learning System with Privacy Protection an...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Longyi Liu Yi Hu Yanqing Zhao Xiyang Zhang Yongze Ma Guiyong Chang Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The data-driven transformation of industrial intelligence is becoming a key focus for the future of smart manufacturing. However, due to concerns about data privacy, the industry often faces a prevalent “data island” problem. Traditional federated learning ensures data privacy and usability to some extent, yet the C/S architecture's design model is susceptible to poisoning attacks, denial-of-service threats, and lacks consensus mechanisms and incentives among participants to ensure fairness in learning. This paper integrates federated learning into blockchain consensus protocols, proposing an FRconsensus algorithm based on model evaluation and stake election, which overcomes issues of passive participation and resource wastage during model training. Simultaneously, it introduces model watermarking and ECC public-key encryption mechanisms to secure parameter transmission. The experimental results demonstrate that the proposed federated learning system achieves superior model convergence. Furthermore, it is more effective in defending against poisoning attacks. In comparison to mainstream federated learning mechanisms based on consensus algorithms, it reduces the election latency by 20%, shortens the consensus latency by 8%, and increases the throughput by 12%.

关键词： Data privacy Federated learning Voting consensus algorithm Throughput Data models consensus protocol Protection Faces Convergence

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Blockchain consensus: Assessing Diverse Mechanisms for Distributed Agreement

Blockchain Consensus: Assessing Diverse Mechanisms for Distr...

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Artificial Intelligence and Emerging Technology (Global AI Summit), International Conference on

作者： Kajal Jain Sanjeev Rana Maharishi Markandeshwar Engineering College Maharishi Markandeshwar (Deemed to be) University India

ISBN: (数字)9798350379716

ISBN: (纸本)9798350379723

Recently, blockchain has become the topic of interest for many industries as traditional approaches to data management are arranged based on new ideas, like decentralized ledgers that cannot be modified. The technology's functionality is powered by consensus algorithms, essential in guaranteeing the integrity of network and transaction validation. In this paper, we have put together a large study of consensus mechanisms and compared them to both open and closed blockchain ecosystems. We investigate the underlying principles of different consensus algorithms. We consider an integrated example on those most popular methods from the Proof-of-Work and Proof-of-Stake that are usually used by public blockchains, through to a BFT (Byzantine Fault Tolerance) one of its derived types which may be commonly found in private blockchain networks. In addition to this, the range of metrics that are used in researching those categories e.g., energy consumption, network scalability and security measures with transaction speed versus confirmation times are also studied. We will conclude by weighting these trade-offs at the architecture level and offer guidelines for when each mechanism is best used across different industries as well as use-cases. Furthermore, our research involves state-of-the-art consensus mechanisms as well including Proof-Of-Authority, Delegated Proof of Stake and hybrid mechanisms aimed at overcoming some of the limitations in existing methods. In this article we explore, some of the new technologies which may play a role in defining how Blockchain evolves and easily Integrates with different sectors.

关键词： Industries Surveys Proof of stake Technological innovation Scalability consensus algorithm Blockchains consensus protocol Security Artificial intelligence

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The Optimal Partition Number Estimation algorithm Based on Variational Inference

The Optimal Partition Number Estimation Algorithm Based on V...

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IET International Radar Conference 2023, IRC 2023

作者： Zhang, Jichuan Jiang, Qi Xu, Liang Wang, Rui Hu, Cheng The Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Advanced Technology Research Institute Beijing Institute of Technology Jinan250300 China The Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839539954

The partition of individual targets into proper clusters is crucial in tracking group targets with complex spatial structures. However, most of the current clustering methods suffer from heavy computation burdens and unfitting a priori knowledge, resulting in the degradation of robustness. This paper proposes an optimal estimate of partition number based on the variational inference for group targets. By maximizing the variational evidence lower bound, which serves as the model-selected criterion, the optimal partition number can be estimated. The K-means++ algorithm is used to initialize the variation iteration. The proposed algorithm does not require a priori information and has low computation complexity, which benefits from the deterministic approximation character of variational inference. The effectiveness of the proposed method is verified by simulation results. © The Institution of Engineering & Technology 2023.

关键词： consensus algorithm

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