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  • Open Access

    ARTICLE

    Traffic Profiling and Secure Virtualized Data Handling of 5G Networks via MinIO Storage

    Khawaja Tahir Mehmood1,*, Muhammad Majid Hussain2

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5643-5670, 2025, DOI:10.32604/cmc.2025.068404 - 23 October 2025

    Abstract In the modern era of 5th generation (5G) networks, the data generated by User Equipments (UE) has increased significantly, with data file sizes varying from modest sensor logs to enormous multimedia files. In modern telecommunications networks, the need for high-end security and efficient management of these large data files is a great challenge for network designers. The proposed model provides the efficient real-time virtual data storage of UE data files (light and heavy) using an object storage system MinIO having inbuilt Software Development Kits (SDKs) that are compatible with Amazon (S3) Application Program Interface (API)… More >

  • Open Access

    ARTICLE

    ScalaDetect-5G: Ultra High-Precision Highly Elastic Deep Intrusion Detection System for 5G Network

    Shengjia Chang, Baojiang Cui*, Shaocong Feng

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3805-3827, 2025, DOI:10.32604/cmes.2025.067756 - 30 September 2025

    Abstract With the rapid advancement of mobile communication networks, key technologies such as Multi-access Edge Computing (MEC) and Network Function Virtualization (NFV) have enhanced the quality of service for 5G users but have also significantly increased the complexity of network threats. Traditional static defense mechanisms are inadequate for addressing the dynamic and heterogeneous nature of modern attack vectors. To overcome these challenges, this paper presents a novel algorithmic framework, SD-5G, designed for high-precision intrusion detection in 5G environments. SD-5G adopts a three-stage architecture comprising traffic feature extraction, elastic representation, and adaptive classification. Specifically, an enhanced Concrete… More >

  • Open Access

    ARTICLE

    Enhancing Bandwidth Allocation Efficiency in 5G Networks with Artificial Intelligence

    Sarmad K. Ibrahim1,*, Saif A. Abdulhussien2, Hazim M. ALkargole1, Hassan H. Qasim1

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5223-5238, 2025, DOI:10.32604/cmc.2025.066548 - 30 July 2025

    Abstract The explosive growth of data traffic and heterogeneous service requirements of 5G networks—covering Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), and Massive Machine Type Communication (mMTC)—present tremendous challenges to conventional methods of bandwidth allocation. A new deep reinforcement learning-based (DRL-based) bandwidth allocation system for real-time, dynamic management of 5G radio access networks is proposed in this paper. Unlike rule-based and static strategies, the proposed system dynamically updates itself according to shifting network conditions such as traffic load and channel conditions to maximize the achievable throughput, fairness, and compliance with QoS requirements. By using… More >

  • Open Access

    ARTICLE

    Intelligent Management of Resources for Smart Edge Computing in 5G Heterogeneous Networks Using Blockchain and Deep Learning

    Mohammad Tabrez Quasim1,*, Khair Ul Nisa1, Mohammad Shahid Husain2, Abakar Ibraheem Abdalla Aadam1, Mohammed Waseequ Sheraz1, Mohammad Zunnun Khan1

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1169-1187, 2025, DOI:10.32604/cmc.2025.062989 - 09 June 2025

    Abstract Smart edge computing (SEC) is a novel paradigm for computing that could transfer cloud-based applications to the edge network, supporting computation-intensive services like face detection and natural language processing. A core feature of mobile edge computing, SEC improves user experience and device performance by offloading local activities to edge processors. In this framework, blockchain technology is utilized to ensure secure and trustworthy communication between edge devices and servers, protecting against potential security threats. Additionally, Deep Learning algorithms are employed to analyze resource availability and optimize computation offloading decisions dynamically. IoT applications that require significant resources… More >

  • Open Access

    ARTICLE

    Advancing 5G Network Applications Lifecycle Security: An ML-Driven Approach

    Ana Hermosilla1,2,*, Jorge Gallego-Madrid1, Pedro Martinez-Julia3, Jordi Ortiz4, Ved P. Kafle3, Antonio Skarmeta1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1447-1471, 2024, DOI:10.32604/cmes.2024.053379 - 27 September 2024

    Abstract As 5th Generation (5G) and Beyond 5G (B5G) networks become increasingly prevalent, ensuring not only network security but also the security and reliability of the applications, the so-called network applications, becomes of paramount importance. This paper introduces a novel integrated model architecture, combining a network application validation framework with an AI-driven reactive system to enhance security in real-time. The proposed model leverages machine learning (ML) and artificial intelligence (AI) to dynamically monitor and respond to security threats, effectively mitigating potential risks before they impact the network infrastructure. This dual approach not only validates the functionality… More >

  • Open Access

    ARTICLE

    Federated Network Intelligence Orchestration for Scalable and Automated FL-Based Anomaly Detection in B5G Networks

    Pablo Fernández Saura1,*, José M. Bernabé Murcia1, Emilio García de la Calera Molina1, Alejandro Molina Zarca2, Jorge Bernal Bernabé1, Antonio F. Skarmeta Gómez1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 163-193, 2024, DOI:10.32604/cmc.2024.051307 - 18 July 2024

    Abstract The management of network intelligence in Beyond 5G (B5G) networks encompasses the complex challenges of scalability, dynamicity, interoperability, privacy, and security. These are essential steps towards achieving the realization of truly ubiquitous Artificial Intelligence (AI)-based analytics, empowering seamless integration across the entire Continuum (Edge, Fog, Core, Cloud). This paper introduces a Federated Network Intelligence Orchestration approach aimed at scalable and automated Federated Learning (FL)-based anomaly detection in B5G networks. By leveraging a horizontal Federated learning approach based on the FedAvg aggregation algorithm, which employs a deep autoencoder model trained on non-anomalous traffic samples to recognize… More >

  • Open Access

    ARTICLE

    Optical Neural Networks: Analysis and Prospects for 5G Applications

    Doaa Sami Khafaga1, Zongming Lv2, Imran Khan3,4, Shebnam M. Sefat5, Amel Ali Alhussan1,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3723-3740, 2023, DOI:10.32604/cmc.2023.039956 - 26 December 2023

    Abstract With the capacities of self-learning, acquainted capacities, high-speed looking for ideal arrangements, solid nonlinear fitting, and mapping self-assertively complex nonlinear relations, neural systems have made incredible advances and accomplished broad application over the final half-century. As one of the foremost conspicuous methods for fake insights, neural systems are growing toward high computational speed and moo control utilization. Due to the inborn impediments of electronic gadgets, it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage. Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways… More >

  • Open Access

    ARTICLE

    An Optimized Approach for Spectrum Utilization in mmWave Massive MIMO 5G Wireless Networks

    Elsaid Md. Abdelrahim1,2, Mona Alduailij3, Mai Alduailij3, Romany F. Mansour4,*, Osama A. Ghoneim5

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1493-1505, 2023, DOI:10.32604/csse.2023.037976 - 28 July 2023

    Abstract Massive multiple-input multiple-output (MIMO) systems that use the millimeter-wave (mm-wave) band have a higher frequency and more antennas, which leads to significant path loss, high power consumption, and server interference. Due to these issues, the spectrum efficiency is significantly reduced, making spectral efficiency improvement an important research topic for 5G communication. Together with communication in the terahertz (THz) bands, mmWave communication is currently a component of the 5G standards and is seen as a solution to the commercial bandwidth shortage. The quantity of continuous, mostly untapped bandwidth in the 30–300 GHz band has presented a rare… More >

  • Open Access

    ARTICLE

    An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

    Ratih Hikmah Puspita1, Jehad Ali1,*, Byeong-hee Roh2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4611-4631, 2023, DOI:10.32604/cmc.2023.033598 - 31 March 2023

    Abstract 5G use cases, for example enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and an ultra-reliable low latency communication (URLLC), need a network architecture capable of sustaining stringent latency and bandwidth requirements; thus, it should be extremely flexible and dynamic. Slicing enables service providers to develop various network slice architectures. As users travel from one coverage region to another area, the call must be routed to a slice that meets the same or different expectations. This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks. Rules of… More >

  • Open Access

    ARTICLE

    Machine Learning Based Classifiers for QoE Prediction Framework in Video Streaming over 5G Wireless Networks

    K. B. Ajeyprasaath, P. Vetrivelan*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1919-1939, 2023, DOI:10.32604/cmc.2023.036013 - 06 February 2023

    Abstract Recently, the combination of video services and 5G networks have been gaining attention in the wireless communication realm. With the brisk advancement in 5G network usage and the massive popularity of three-dimensional video streaming, the quality of experience (QoE) of video in 5G systems has been receiving overwhelming significance from both customers and service provider ends. Therefore, effectively categorizing QoE-aware video streaming is imperative for achieving greater client satisfaction. This work makes the following contribution: First, a simulation platform based on NS-3 is introduced to analyze and improve the performance of video services. The simulation… More >

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