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43rd Chinese Control Conference, CCC 2024

作者： Xiao, Jvlong Liu, Kexin School of Automation Science and Electrical Engineering Beijing100191 China

ISBN: (纸本)9789887581581

This paper proposes a distributed quantified shape-formation algorithm that incorporates communication quantification in consensus negotiation during motion control. This algorithm encourages all agents to reach a consensus on the location and orientation of the target shape within limited communication bandwidth, which reduces the bandwidth required for communication greatly. The quantified shape-formation algorithm guides all agents to complete the shape-formation task while negotiating the target shape with each other. Moreover, the algorithm is extended to the under-actuated unmanned ground vehicle (UGV) model considering its nonholonomic constraints, expanding the application scenarios of this algorithm. Numerical simulations are conducted to demonstrate the algorithm's effectiveness: The consensus on the location and orientation of the target shape can be achieved using limited communication bandwidth. All of the agents are converged to the user-defined shape and are forced as dispersedly as possible to ensure the target area is filled. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： consensus algorithm

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Proportionate Conjugate Gradient algorithm for Sparse Systems 15

Proportionate Conjugate Gradient Algorithm for Sparse System...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dhande, Shila Das, Rajib Lochan DAIICT Department of Electronics and Communication Gandhinagar India KJSCE Department of Electronics and Computer Mumbai India

ISBN: (纸本)9798350370249

For colored input, the Recursive Least Square (RLS) technique is employed to achieve a higher computational complexity but a faster convergence rate. Recently, For lesser computational complexity, the conjugate gradient (CG) algorithm has replaced the RLS algorithm as it yields a similar convergence rate with. In this paper, a sparse CG algorithm is proposed by introducing a proportional gain matrix in its update equation to obtain further improvement in the convergence rate for identifying sparse systems with colored inputs. The proposed algorithm provides a better convergence rate as the active taps (AT) get higher step size and thus converge fast. Incorporation of the gain function is made tactfully to obtain improvement in its overall performance. Simulation findings demonstrate that the suggested technique considerably increases the steady-state error and convergence rate. © 2024 IEEE.

关键词： consensus algorithm

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Proportional Power-Sharing Control of Distributed Generators in Microgrids

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2022年第2期30卷 481-494页

作者： Aalipour, Farzad Das, Tuhin Univ Cent Florida Dept Mech & Aerosp Engn Orlando FL 32816 USA

This research addresses distributed proportional power-sharing of inverter-based distributed generators (DGs) in microgrids under variations in the maximum power capacity of DGs. A microgrid can include renewable energy resources such as wind turbines, solar panels, fuel cells, etc. The intermittent nature of such energy resources causes variations in their maximum power capacities. Since DGs in microgrids can be regarded as multiagent-systems (MASs), a consensus algorithm is designed to have the DGs to generate their output power in proportion to their maximum capacities under capacity fluctuations. A change in power capacity of a DG triggers the consensus algorithm, which uses a communication map at the cyber layer to estimate the corresponding change. The convergence rate of the algorithm is analytically established and bounds on allowable capacity fluctuations are derived based on practical constraints. During the transient time of reaching a consensus, the delivered power may not match the load power demand. To eliminate this mismatch, a control law is augmented that consists of a finite-time consensus algorithm embedded within the overarching power-sharing consensus algorithm. The effectiveness of the distributed controller is assessed through simulation of a microgrid consisting of a realistic model of inverter-based DGs. Details of the microgrid model, its controller structures, and a comprehensive list of parameters are provided.

关键词： Microgrids consensus algorithm Voltage control Transient analysis Convergence Renewable energy sources Delays consensus distributed control eigenvalue perturbation finite-time consensus inverter-based microgrid proportional power-sharing renewable energy transient control

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Zero trust in edge computing environment: a blockchain based practical scheme

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第4期19卷 4196-4216页

作者： Li, Dawei Zhang, Enzhun Lei, Ming Song, Chunxiao Nanjing Inst Technol Sch Comp Engn Nanjing 211167 Peoples R China Nanjing Inst Technol Energy Res Inst Nanjing 211167 Peoples R China NARI Grp Corp State Grid Elect Power Res Inst Nanjing 211106 Peoples R China

Edge computing offloads the data processing capacity to the user side, provides flexible and efficient computing services for the development of smart city, and brings many security challenges. Aiming at the problems of fuzzy boundary security protection and dynamic identity authentication in the edge computing environment in smart city, the zero trust architecture based on blockchain is studied, and a digital identity model and dynamic authentication scheme of edge computing nodes based on distributed ledger are proposed. Firstly, a digital identity model of two-way authentication between edge computing node and sensing terminal is established to realize fine-grained authorization and access control in edge computing. Secondly, based on the identity data and behavior log bookkeeping on the chain, the quantification of trust value, trust transmission and update are realized, and the traceability of security events is improved. Finally, based on the improved RAFT consensus algorithm, the multi-party consensus and consistency accounting in the authentication process are realized. Simulation results show that this scheme can meet the requirements of zero trust verification in edge computing environment, and has good efficiency and robustness.

关键词： blockchain Internet of things zero trust edge computing secret sharing consensus algorithm

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AEchain: A Lightweight Blockchain for IoT Applications

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IEEE CONSUMER ELECTRONICS MAGAZINE 2022年第2期11卷 64-76页

作者： Khan, Safiullah Lee, Wai-Kong Hwang, Seong Oun Gachon Univ Seongnam South Korea

IoT nodes comprise of sensors and embedded resource-constrained systems. On the other hand, blockchain is regarded as computationally expensive due to the consensus algorithms. Therefore, it is challenging to apply blockchain to an IoT system. This work presents a unique concept that integrates blockchain with lightweight cryptographic solutions targeting resource-constrained IoT sensor nodes. In particular, proof-of-authentication utilizing a lightweight authenticated encryption (AE) scheme to achieve consensus is proposed. At sensor nodes, a tag is generated based on sensor data, which is then broadcast to the network. Upon authentication from the cluster head node (e.g., a gateway), the block is hashed using the lightweight hash function and added to the blockchain. The proposed solution can be implemented in software (e.g., microcontroller) or hardware platform (e.g., FPGA, ASIC). Experimental results show that lightweight authentication can perform 1.34 M authentications per-second with only 6.55 k lookup tables (LUTs) on the Spartan-6 FPGA platform. This high-throughput authentication can speed up the consensus in blockchain, utilizing few resources and making it very suitable for applications in IoT sensor nodes.

关键词： Internet of Things Blockchain Hardware Authentication Sensors consensus algorithm Physical unclonable function

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A Batch-to-Online Transformation under Random-Order Model 37

A Batch-to-Online Transformation under Random-Order Model

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37th Conference on Neural Information Processing Systems (NeurIPS)

作者： Dong, Jing Yoshida, Yuichi Chinese Univ Hong Kong Shenzhen Peoples R China Natl Inst Informat Shenzhen Peoples R China

ISBN: (纸本)9781713899921

We introduce a transformation framework that can be utilized to develop online algorithms with low epsilon-approximate regret in the random-order model from offline approximation algorithms. We first give a general reduction theorem that transforms an offline approximation algorithm with low average sensitivity to an online algorithm with low epsilon-approximate regret. We then demonstrate that offline approximation algorithms can be transformed into a low-sensitivity version using a coreset construction method. To showcase the versatility of our approach, we apply it to various problems, including online (k, z)-clustering, online matrix approximation, and online regression, and successfully achieve polylogarithmic epsilon-approximate regret for each problem. Moreover, we show that in all three cases, our algorithm also enjoys low inconsistency, which may be desired in some online applications.

关键词： consensus algorithm

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Enhancing Blockchain Network Scalability Through Parallelization and Aggregation Techniques: A Survey

Enhancing Blockchain Network Scalability Through Paralleliza...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Olusegun, Ruth Yang, Bo Bowie State Univ Dept Comp Sci Bowie MD 20715 USA

ISBN: (纸本)9798350361513;9798350372304

Blockchain is known for its potential to create high transparency, decentralization, and unprecedented security. However, it is still confronted with scalability problems which pose a significant barrier to its wide adoption. Scalability constraints result in high transaction fees, high latency, and low throughput in many blockchain networks. To handle this bottleneck, several scaling solutions have been developed. Recent research has explored hybridization of scaling solutions, paving the way for major scaling innovations. This article analyzes how parallel and aggregated scaling methods can be integrated to achieve exponential scalability in blockchain networks. We examine fundamental concepts, techniques, implementation strategies, and then propose ZKShard, a paradigm based on zero-knowledge proofs and sharding. In the proposed system, key components such as parallelization, communication, aggregation, user experience and interaction were examined. We also explored ZKShard applications in domains such as Decentralized Finance (DeFi), New Financial Technologies (NFTs), and Supply Chain Management. Finally, we discussed research challenges and future directions based on security, cross-shard communication, data availability, smart contracts, and consensus mechanism.

关键词： Zero-knowledge proof Rollup Sharding Scalability consensus algorithm

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DBSCAN parallelization by spatial dataset division and hyperparameter adjustment 1

DBSCAN parallelization by spatial dataset division and hyper...

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1st International Workshop on Bioinformatics and Applied Information Technologies, BAIT 2024

作者： Romanuke, Vadim Pavlov, Sergii Yaremko, Svitlana Guralnyk, Artem Smetaniuk, Olena Vinnytsia Institute of Trade and Economics State University of Trade and Economics Soborna str. 87 Vinnytsia21050 Ukraine Vinnytsia National Technical University Khmelnytske sh. 95 Vinnytsia21021 Ukraine

An approach to parallelizing the DBSCAN algorithm without losing in accuracy is presented to further improve quality of arbitrary‐shape clustering. The dataset is divided into a number of subsets, one of which should be labeled to adjust the DBSCAN hyperparameters - the neighborhood radius and minimum‐neighbors number. The neighborhood radius, set to a minimum, is adjusted first, where the original DBSCAN is applied to a subset of points with known ground truth labels. While the current accuracy of clustering is not improved, the neighborhood radius is increased by an increment step. The original DBSCAN algorithm is applied with the best neighborhood radius to the remaining subsets. The minimum‐neighbors number, set to 3, is adjusted second by the best neighborhood radius. Compared to the performance of the original DBSCAN algorithm, the parallelized DBSCAN performs more accurately being extremely fast. As the dataset size increases and the number of clusters increases, one by one or together, the parallelized DBSCAN outperforms the original DBSCAN more. However, the DBSCAN parallelization by spatial dataset division and hyperparameter adjustment is less efficient on datasets with more complex structure. Nevertheless, the average speedup exceeds 80 times for planar datasets and exceeds 300 times for three‐dimensional datasets. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： consensus algorithm

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Adaptive Dynamic Event-triggered algorithm for Economic Dispatch Problem with Discrete Communication and Control 43

Adaptive Dynamic Event-triggered Algorithm for Economic Disp...

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43rd Chinese Control Conference, CCC 2024

作者： Cheng, Zuxia Chu, Hongjun Ma, Zhuo Institute of Advanced Technology for Carbon Neutrality Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9789887581581

This article investigates the distributed economic dispatch problem of smart grid under discrete communication and algorithm updates. By introducing virtual adaptive gains and time-varying threshold dynamics, a novel adaptive dynamic event-triggered distributed optimization algorithm is proposed for balancing supply and demand at a minimum of economic cost. Compared with existing algorithms, the prominent advantage of this algorithm is that both communication among generations and algorithm updates are only at event-triggered instances, saving communication resources and control efforts. Strict proof shows that the proposed algorithm copes with distributed economic dispatch problem, and Zeno behavior can be excluded. At last, its effectiveness is validated by a simulation example. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： consensus algorithm

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Replicable Learning of Large-Margin Halfspaces 41

Replicable Learning of Large-Margin Halfspaces

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41st International Conference on Machine Learning, ICML 2024

作者： Kalavasis, Alkis Karbasi, Amin Larsen, Kasper Green Velegkas, Grigoris Zhou, Felix Yale University United States Google Research United States Aarhus University Denmark

We provide efficient replicable algorithms for the problem of learning large-margin halfspaces. Our results improve upon the algorithms provided by Impagliazzo, Lei, Pitassi, and Sorrell (STOC, 2022). We design the first dimension-independent replicable algorithms for this task which runs in polynomial time, is proper, and has strictly improved sample complexity compared to the one achieved by Impagliazzo et al. (2022) with respect to all the relevant parameters. Moreover, our first algorithm has sample complexity that is optimal with respect to the accuracy parameter Ε. We also design an SGD-based replicable algorithm that, in some parameters' regimes, achieves better sample and time complexity than our first algorithm. Departing from the requirement of polynomial time algorithms, using the DP-to-Replicability reduction of Bun, Gaboardi, Hopkins, Impagliazzo, Lei, Pitassi, Sivakumar, and Sorrell (STOC, 2023), we show how to obtain a replicable algorithm for large-margin halfspaces with improved sample complexity with respect to the margin parameter τ, but running time doubly exponential in 1/τ2 and worse sample complexity dependence on Ε than one of our previous algorithms. We then design an improved algorithm with better sample complexity than all three of our previous algorithms and running time exponential in 1/τ2 Copyright 2024 by the author(s)

关键词： consensus algorithm

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