ICT Express最新文献_第2页

Lightweight federated learning-based intrusion detection system for industrial internet of things 面向工业物联网的轻量级联邦学习入侵检测系统

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.05.002

Sun-Jin Lee, Il-Gu Lee

引用次数: 0

A novel ensemble XGBoost and deep Q-network for pregnancy risk prediction on multi-class imbalanced datasets 基于XGBoost和deep Q-network的多类不平衡数据妊娠风险预测

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.05.010

Kurnianingsih , Sou Nobukawa , Melyana Nurul Widyawati , Cipta Pramana , Nurseno Bayu Aji , Afandi Nur Aziz Thohari , Dwiana Hendrawati , Eri Sato-Shimokawara , Naoyuki Kubota

引用次数: 0

RIS-enabled cooperative symbiotic radio communications with movable antennas 具有可移动天线的riss支持的协作共生无线电通信

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.04.013

Bin Lyu, Wenqing Hong

引用次数: 0

Using large language models for semantic interoperability: A systematic literature review 使用大型语言模型实现语义互操作性：系统的文献综述

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.06.011

Bilal Abu-Salih , Salihah Alotaibi , Albandari Lafi Alanazi , Ruba Abu Khurma , Bashar Al-Shboul , Ansar Khouri , Mohammed Aljaafari

引用次数: 0

MSS-TCP: A congestion control algorithm for boosting TCP performance in mmwave cellular networks MSS-TCP：一种在毫米波蜂窝网络中提高TCP性能的拥塞控制算法

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.05.005

Omar Imhemed Alramli , Zurina Mohd Hanapi , Mohamed Othman , Normalia Samian , Idawaty Ahmad

{"title":"MSS-TCP: A congestion control algorithm for boosting TCP performance in mmwave cellular networks","authors":"Omar Imhemed Alramli , Zurina Mohd Hanapi , Mohamed Othman , Normalia Samian , Idawaty Ahmad","doi":"10.1016/j.icte.2025.05.005","DOIUrl":"10.1016/j.icte.2025.05.005","url":null,"abstract":"<div><div>The increasing demand for high-speed, low-latency applications, especially with 5G mmWave technology, has led to challenges in TCP performance due to signal blockages, small buffers, and high Packet Error Rates (PERs). Existing congestion control algorithms (CCAs) struggle to fully utilize available bandwidth under these conditions. This paper proposes MSS-TCP, a novel congestion control algorithm designed for mmWave networks. MSS-TCP dynamically adjusts the congestion window (cwnd) based on the maximum segment size (MSS) and round-trip time (RTT), improving bandwidth utilization and congestion adaptability. The simulation results using the ns-3 network simulator show that MSS-TCP outperforms state-of-the-art CCAs, including NewReno, HighSpeed, CUBIC, and Bottleneck Bandwidth and Round-trip propagation time (BBR), and Fuzzy Logic-based (FB-TCP), particularly when the buffer matches the bandwidth-delay product (BDP), achieving a 24.26% to 45.43% improvement in throughput compared to BBR while maintaining low latency. These findings demonstrate that MSS-TCP enhances TCP performance in 5G mmWave networks, making it a promising solution for next-generation wireless communication.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 4","pages":"Pages 631-635"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EntUn: Mitigating the forget-retain dilemma in unlearning via entropy EntUn：通过熵来缓解遗忘-保留困境

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.06.007

Dahuin Jung

引用次数: 0

Federated learning and TinyML on IoT edge devices: Challenges, advances, and future directions IoT边缘设备上的联合学习和TinyML：挑战、进展和未来方向

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.06.008

Montaser N.A. Ramadan , Mohammed A.H. Ali , Shin Yee Khoo , Mohammad Alkhedher

{"title":"Federated learning and TinyML on IoT edge devices: Challenges, advances, and future directions","authors":"Montaser N.A. Ramadan , Mohammed A.H. Ali , Shin Yee Khoo , Mohammad Alkhedher","doi":"10.1016/j.icte.2025.06.008","DOIUrl":"10.1016/j.icte.2025.06.008","url":null,"abstract":"<div><div>This paper examines the integration of Federated Learning (FL), TinyML, and IoT in resource-constrained edge devices, highlighting key challenges and opportunities. It reviews FL and TinyML frameworks with a focus on communication, privacy, accuracy, efficiency, and memory constraints. We propose a novel FL-IoT framework that combines over-the-air (OTA) AI model updates, LoRa-based distributed communication, and lossless data compression techniques such as Run-Length Encoding (RLE), Huffman coding, and LZW to reduce transmission cost, optimize local processing, and maintain data privacy. The framework features Raspberry Pi-based aggregation nodes and microcontroller-based IoT clients, enabling scalable, low-power learning across heterogeneous devices. Evaluation includes memory usage, communication cost, energy consumption, and accuracy trade-offs across multiple FL scenarios. Results show improved scalability and significant power savings compared to baseline FL setups. The proposed framework is particularly impactful in applications such as smart agriculture, healthcare, and smart cities. Future directions for real-time, privacy-preserving edge intelligence are discussed.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 4","pages":"Pages 754-768"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven integrated sensing and communication: Recent advances, challenges, and future prospects 数据驱动的集成传感和通信：最新进展、挑战和未来展望

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.06.010

Hammam Salem , Haleema Sadia , MD Muzakkir Quamar , Adeb Magad , Mohammed Elrashidy , Nasir Saeed , Mudassir Masood

{"title":"Data-driven integrated sensing and communication: Recent advances, challenges, and future prospects","authors":"Hammam Salem , Haleema Sadia , MD Muzakkir Quamar , Adeb Magad , Mohammed Elrashidy , Nasir Saeed , Mudassir Masood","doi":"10.1016/j.icte.2025.06.010","DOIUrl":"10.1016/j.icte.2025.06.010","url":null,"abstract":"<div><div>The integration of integrated sensing and communication (ISAC) with artificial intelligence (AI)-driven techniques has emerged as a transformative research frontier, attracting significant interest from both academia and industry. As sixth-generation (6G) networks advance to support ultra-reliable, low-latency, and high-capacity applications, machine learning (ML) has become a critical enabler for optimizing ISAC functionalities. Recent advancements in deep learning (DL) and deep reinforcement learning (DRL) have demonstrated immense potential in enhancing ISAC-based systems across diverse domains, including intelligent vehicular networks, autonomous mobility, unmanned aerial vehicles based communications, radar sensing, localization, millimeter wave/terahertz communication, and adaptive beamforming. However, despite these advancements, several challenges persist, such as real-time decision-making under resource constraints, robustness in adversarial environments, and scalability for large-scale deployments. This paper provides a comprehensive review of ML-driven ISAC methodologies, analyzing their impact on system design, computational efficiency, and real-world implementations, while also discussing existing challenges and future research directions to explore how AI can further enhance ISAC’s adaptability, resilience, and performance in next-generation wireless networks. By bridging theoretical advancements with practical implementations, this paper serves as a foundational reference for researchers, engineers, and industry stakeholders, aiming to leverage AI’s full potential in shaping the future of intelligent ISAC systems within the 6G ecosystem.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 4","pages":"Pages 790-808"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optical wireless communications for next-generation radio access networks 用于下一代无线接入网的光无线通信

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.04.016

Abdul Wadud , Anas Basalamah

{"title":"Optical wireless communications for next-generation radio access networks","authors":"Abdul Wadud , Anas Basalamah","doi":"10.1016/j.icte.2025.04.016","DOIUrl":"10.1016/j.icte.2025.04.016","url":null,"abstract":"<div><div>High-speed and high-bandwidth capabilities provided by free space optical wireless communication (FSO-WC) improve communication technologies with better channel security. With its high carrier frequency, wide bandwidth, and use of unlicensed spectrum, FSO has been identified by researchers looking into innovations in next-generation wireless communications as a promising way to deliver ultrafast data links to meet the growing demands for massive connectivity and high data rates in a variety of 6G applications, such as cellular wireless backhauls and heterogeneous networks. However, issues like atmospheric turbulence, absorption, and scattering have a major impact on the system’s performance by raising the bit error rate (BER) and symbol error rate (SER). In order to tackle these problems, this paper looks at Deep Neural Network (DNN) models, particularly Multi-Layer Perceptrons (MLP) and Convolutional Neural Networks (CNN). We experiment DNN-based equalizer in context of Open Radio Access Network (O-RAN), which aims to minimize SER and BER. According to the investigation, CNNs use more processing resources than MLPs, although offering superior error reduction. Our investigation shows that FSO can be adopted in high data rate front haul between the distributed units (DUs) and radio units (RUs).</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 4","pages":"Pages 721-727"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Efficient Resource Allocation Mechanism with Fuzzy C-Means and Adaptive RNNs for D2D Communications in Cellular Networks 基于模糊c均值和自适应rnn的蜂窝网络D2D通信有效资源分配机制

IF 4.2 3区计算机科学

ICT Express Pub Date : 2025-08-01 DOI: 10.1016/j.icte.2025.05.003

Sambi Reddy Gottam, Udit Narayana Kar

{"title":"An Efficient Resource Allocation Mechanism with Fuzzy C-Means and Adaptive RNNs for D2D Communications in Cellular Networks","authors":"Sambi Reddy Gottam, Udit Narayana Kar","doi":"10.1016/j.icte.2025.05.003","DOIUrl":"10.1016/j.icte.2025.05.003","url":null,"abstract":"<div><div>Direct communication links between nearby users can be established via device-to-device (D2D) communications, eliminating the need for a base station (BS) or remaining core networks. The D2D users’ transmission power is lower than the BS’s traffic burden. Nonorthogonal multiple access (NOMA) expertise allows a transmitter to direct multiple impulses at the same wavelength by power superposition, possibly enhancing spectrum efficiency. In this work, an adaptive recurrent neural network (ARNN) is developed to effectively handle the nonlinearity of transmission powers and channel diversity. Furthermore, a method called fuzzy C-means clustering (FCMC) is designed to group users on different subcarriers with different strengths. For spectrum utilization to improve, clustering is necessary. The advanced coati optimization algorithm (ACOA) is subsequently utilized to assign assets. The Levy Flight (LF) function is taken into consideration when choosing the weight value in the Coati Optimization Algorithm (COA). The simulation findings demonstrate that our method is better at increasing system throughput while meeting users’ file requests. This method enables the efficient use of resources and power control in interactions between devices. The proposed method is implemented in MATLAB, and its performance is evaluated via performance measures. It is compared with conventional approaches. The results indicate that the suggested method achieves superior outage probability values across different user counts, with values of 0.99465 for 40 users, 0.99946 for 60 users, 0.99946 for 80 users, and 0.999446 for 100 users. Comparatively, the Recurrent Neural Network-Honey Badger Algorithm (RNN-HBA) achieved slightly lower outage probabilities, whereas the Deep Belief Network (DBN) and Particle Swarm Optimization (PSO) demonstrated more significant variations, especially with a greater number of users.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 4","pages":"Pages 743-753"},"PeriodicalIF":4.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0