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  • Open Access

    ARTICLE

    Research on Grid-Connected Control Strategy of Distributed Generator Based on Improved Linear Active Disturbance Rejection Control

    Xin Mao*, Hongsheng Su, Jingxiu Li

    Energy Engineering, Vol.121, No.12, pp. 3929-3951, 2024, DOI:10.32604/ee.2024.057106 - 22 November 2024

    Abstract The virtual synchronous generator (VSG) technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources. However, the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response. In light of the issues above, a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control (ILADRC) is put forth for consideration. Firstly, an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop; then, the… More >

  • Open Access

    ARTICLE

    Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Razaz Waheeb Attar4, Farman Ali5,*, Ahmed Alhomoud6, Babar Shah7

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2357-2394, 2024, DOI:10.32604/cmc.2024.056694 - 18 November 2024

    Abstract Ad hoc networks offer promising applications due to their ease of use, installation, and deployment, as they do not require a centralized control entity. In these networks, nodes function as senders, receivers, and routers. One such network is the Flying Ad hoc Network (FANET), where nodes operate in three dimensions (3D) using Unmanned Aerial Vehicles (UAVs) that are remotely controlled. With the integration of the Internet of Things (IoT), these nodes form an IoT-enabled network called the Internet of UAVs (IoU). However, the airborne nodes in FANET consume high energy due to their payloads and… More >

  • Open Access

    ARTICLE

    Trust Score-Based Malicious Vehicle Detection Scheme in Vehicular Network Environments

    Wenming Wang1,2,3,*, Zhiquan Liu1, Shumin Zhang1, Guijiang Liu1

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2517-2545, 2024, DOI:10.32604/cmc.2024.055184 - 18 November 2024

    Abstract Advancements in the vehicular network technology enable real-time interconnection, data sharing, and intelligent cooperative driving among vehicles. However, malicious vehicles providing illegal and incorrect information can compromise the interests of vehicle users. Trust mechanisms serve as an effective solution to this issue. In recent years, many researchers have incorporated blockchain technology to manage and incentivize vehicle nodes, incurring significant overhead and storage requirements due to the frequent ingress and egress of vehicles within the area. In this paper, we propose a distributed vehicular network scheme based on trust scores. Specifically, the designed architecture partitions multiple More >

  • Open Access

    ARTICLE

    Distributed Federated Split Learning Based Intrusion Detection System

    Rasha Almarshdi1,2,*, Etimad Fadel1, Nahed Alowidi1, Laila Nassef1

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 949-983, 2024, DOI:10.32604/iasc.2024.056792 - 31 October 2024

    Abstract The Internet of Medical Things (IoMT) is one of the critical emerging applications of the Internet of Things (IoT). The huge increases in data generation and transmission across distributed networks make security one of the most important challenges facing IoMT networks. Distributed Denial of Service (DDoS) attacks impact the availability of services of legitimate users. Intrusion Detection Systems (IDSs) that are based on Centralized Learning (CL) suffer from high training time and communication overhead. IDS that are based on distributed learning, such as Federated Learning (FL) or Split Learning (SL), are recently used for intrusion… More >

  • Open Access

    ARTICLE

    Distributed Robust Scheduling Optimization of Wind-Thermal-Storage System Based on Hybrid Carbon Trading and Wasserstein Fuzzy Set

    Gang Wang*, Yuedong Wu, Xiaoyi Qian, Yi Zhao

    Energy Engineering, Vol.121, No.11, pp. 3417-3435, 2024, DOI:10.32604/ee.2024.052268 - 21 October 2024

    Abstract A robust scheduling optimization method for wind–fire storage system distribution based on the mixed carbon trading mechanism is proposed to improve the rationality of carbon emission quota allocation while reducing the instability of large-scale wind power access systems. A hybrid carbon trading mechanism that combines short-term and long-term carbon trading is constructed, and a fuzzy set based on Wasserstein measurement is proposed to address the uncertainty of wind power access. Moreover, a robust scheduling optimization method for wind–fire storage systems is formed. Results of the multi scenario comparative analysis of practical cases show that the More >

  • Open Access

    ARTICLE

    A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

    Liang Zeng1,2,3, Ziyang Ding1, Junyang Shi1, Shanshan Wang1,2,3,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

    Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

  • Open Access

    ARTICLE

    Research on Tensor Multi-Clustering Distributed Incremental Updating Method for Big Data

    Hongjun Zhang1,2, Zeyu Zhang3, Yilong Ruan4, Hao Ye5,6, Peng Li1,*, Desheng Shi1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1409-1432, 2024, DOI:10.32604/cmc.2024.055406 - 15 October 2024

    Abstract The scale and complexity of big data are growing continuously, posing severe challenges to traditional data processing methods, especially in the field of clustering analysis. To address this issue, this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update (BDTMCDIncreUpdate), which combines distributed computing, storage technology, and incremental update techniques to provide an efficient and effective means for clustering analysis. Firstly, the original dataset is divided into multiple sub-blocks, and distributed computing resources are utilized to process the sub-blocks in parallel, enhancing efficiency. Then, initial clustering is performed on each sub-block… More >

  • Open Access

    ARTICLE

    Research on IPFS Image Copyright Protection Method Based on Blockchain

    Xin Cong, Lanjin Feng*, Lingling Zi

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 663-684, 2024, DOI:10.32604/cmc.2024.054372 - 15 October 2024

    Abstract In the digital information age, distributed file storage technologies like the InterPlanetary File System (IPFS) have gained considerable traction as a means of storing and disseminating media content. Despite the advantages of decentralized storage, the proliferation of decentralized technologies has highlighted the need to address the issue of file ownership. The aim of this paper is to address the critical issues of source verification and digital copyright protection for IPFS image files. To this end, an innovative approach is proposed that integrates blockchain, digital signature, and blind watermarking. Blockchain technology functions as a decentralized and… More >

  • Open Access

    ARTICLE

    Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

    Khawaja Tahir Mehmood1,2,*, Shahid Atiq1, Intisar Ali Sajjad3, Muhammad Majid Hussain4, Malik M. Abdul Basit2

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1673-1708, 2024, DOI:10.32604/cmes.2024.053903 - 27 September 2024

    Abstract Software-Defined Networking (SDN), with segregated data and control planes, provides faster data routing, stability, and enhanced quality metrics, such as throughput (Th), maximum available bandwidth (Bd(max)), data transfer (DTransfer), and reduction in end-to-end delay (D(E-E)). This paper explores the critical work of deploying SDN in large­scale Data Center Networks (DCNs) to enhance its Quality of Service (QoS) parameters, using logically distributed control configurations. There is a noticeable increase in Delay(E-E) when adopting SDN with a unified (single) control structure in big DCNs to handle Hypertext Transfer Protocol (HTTP) requests causing a reduction in network quality parameters (Bd(max), Th, DTransfer, D(E-E),… More > Graphic Abstract

    Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

  • Open Access

    ARTICLE

    Quantitative Identification of Delamination Damage in Composite Structure Based on Distributed Optical Fiber Sensors and Model Updating

    Hao Xu1, Jing Wang2, Rubin Zhu2, Alfred Strauss3, Maosen Cao4, Zhanjun Wu1,*

    Structural Durability & Health Monitoring, Vol.18, No.6, pp. 785-803, 2024, DOI:10.32604/sdhm.2024.051393 - 20 September 2024

    Abstract Delamination is a prevalent type of damage in composite laminate structures. Its accumulation degrades structural performance and threatens the safety and integrity of aircraft. This study presents a method for the quantitative identification of delamination identification in composite materials, leveraging distributed optical fiber sensors and a model updating approach. Initially, a numerical analysis is performed to establish a parameterized finite element model of the composite plate. Then, this model subsequently generates a database of strain responses corresponding to damage of varying sizes and locations. The radial basis function neural network surrogate model is then constructed More >

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