Nujud Aloshban^*, Abeer A.K. Alharbi

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4795-4826, 2025, DOI:10.32604/cmc.2025.067523 - 23 October 2025

Abstract The rise of 6G networks and the exponential growth of smart city infrastructures demand intelligent, real-time traffic forecasting solutions that preserve data privacy. This paper introduces NeuroCivitas, a federated deep learning framework that integrates Convolutional Neural Networks (CNNs) for spatial pattern recognition and Long Short-Term Memory (LSTM) networks for temporal sequence modeling. Designed to meet the adaptive intelligence requirements of cognitive cities, NeuroCivitas leverages Federated Averaging (FedAvg) to ensure privacy-preserving training while significantly reducing communication overhead—by 98.7% compared to centralized models. The model is evaluated using the Kaggle Traffic Prediction Dataset comprising 48,120 hourly records… More >

Mohammed Naif Alatawi^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 695-727, 2025, DOI:10.32604/cmc.2025.066606 - 29 August 2025

Abstract Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0. Latency, privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems. We demonstrate that, to overcome these challenges, for instance, the EdgeGuard-IoT framework, a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid, is needed on the edge to integrate Secure Federated Learning (SFL) and Adaptive Anomaly Detection (AAD). With ultra-reliable low latency communication (URLLC) of 6G, artificial intelligence-based network orchestration, and massive machine type… More >

Venkata Satya Suresh kumar Kondeti¹, Raghavendra Kulkarni¹, Binu Sudhakaran Pillai², Surendran Rajendran^3,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4973-4995, 2025, DOI:10.32604/cmc.2025.066428 - 30 July 2025

Abstract Next-generation 6G networks seek to provide ultra-reliable and low-latency communications, necessitating network designs that are intelligent and adaptable. Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures. Nonetheless, sustaining elevated Quality of Service (QoS) in dynamic, resource-limited systems poses significant hurdles. This study introduces an innovative packet-based proactive end-to-end (ETE) resource management system that facilitates network slicing with improved resilience and proactivity. To get around the drawbacks of conventional reactive systems, we develop a cost-efficient slice provisioning architecture that takes into account limits on radio, processing, and… More >

A. F. M. Shahen Shah^1,*, Muhammet Ali Karabulut², Abu Kamruzzaman³, Dalal Alharthi⁴, Phillip G. Bradford⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 1981-2013, 2025, DOI:10.32604/cmc.2025.064028 - 03 July 2025

Abstract The advent of 6G wireless technology, which offers previously unattainable data rates, very low latency, and compatibility with a wide range of communication devices, promises to transform the networking environment completely. The 6G wireless proposals aim to expand wireless communication’s capabilities well beyond current levels. This technology is expected to revolutionize how we communicate, connect, and use the power of the digital world. However, maintaining secure and efficient data management becomes crucial as 6G networks grow in size and complexity. This study investigates blockchain clustering and artificial intelligence (AI) approaches to ensure a reliable and… More >

Omar Alnajar^*, Ahmed Barnawi

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3861-3897, 2025, DOI:10.32604/cmes.2025.065833 - 30 June 2025

Abstract The Tactile Internet of Things (TIoT) promises transformative applications—ranging from remote surgery to industrial robotics—by incorporating haptic feedback into traditional IoT systems. Yet TIoT’s stringent requirements for ultra-low latency, high reliability, and robust privacy present significant challenges. Conventional centralized Federated Learning (FL) architectures struggle with latency and privacy constraints, while fully distributed FL (DFL) faces scalability and non-IID data issues as client populations expand and datasets become increasingly heterogeneous. To address these limitations, we propose a Clustered Distributed Federated Learning (CDFL) architecture tailored for a 6G-enabled TIoT environment. Clients are grouped into clusters based on… More >

Hayder Faeq Alhashimi¹, Mhd Nour Hindia¹, Kaharudin Dimyati^1,*, Effariza Binti Hanafi¹, Feras Zen Alden², Faizan Qamar³, Quang Ngoc Nguyen^4,5,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3585-3622, 2025, DOI:10.32604/cmc.2025.062867 - 19 May 2025

Abstract The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks. Artificial Intelligence (AI) advancements have contributed to the development of several innovative technologies by providing sophisticated specific AI mathematical models such as machine learning models, deep learning models, and hybrid models. Furthermore, intelligent resource management allows for self-configuration and autonomous decision-making capabilities of AI methods, which in turn improves the performance of 6G networks. Hence, 6G networks rely substantially on AI methods to manage resources. This paper comprehensively surveys the recent… More >

Syed Zain Ul Abideen¹, Mian Muhammad Kamal^2,*, Eaman Alharbi³, Ashfaq Ahmad Malik⁴, Wadee Alhalabi⁵, Muhammad Shahid Anwar^6,*, Liaqat Ali⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2191-2210, 2025, DOI:10.32604/cmes.2025.061744 - 03 March 2025

Abstract The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet of Things (IoT) applications, particularly in terms of ultra-reliable, secure, and energy-efficient communication. This study explores the integration of Reconfigurable Intelligent Surfaces (RIS) into IoT networks to enhance communication performance. Unlike traditional passive reflector-based approaches, RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes, addressing critical IoT challenges such as energy efficiency, limited communication range, and double-fading effects in backscatter communication. We propose a novel computational framework that combines… More >

Usman Mahmood Malik¹, Muhammad Awais Javed², Ahmad Naseem Alvi², Mohammed Alkhathami^3,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2255-2274, 2025, DOI:10.32604/cmc.2025.061254 - 17 February 2025

Abstract Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing, and data storage services which are required for several 6G applications. Artificial Intelligence (AI) algorithms will be an integral part of 6G systems and efficient task offloading techniques using fog computing will improve their performance and reliability. In this paper, the focus is on the scenario of Partial Offloading of a Task to Multiple Helpers (POMH) in which larger tasks are divided into smaller subtasks and processed in parallel, hence expediting task completion. However, using POMH presents challenges… More >

Sagar Kavaiya¹, Hiren Mewada^2,*, Sagarkumar Patel³, Dharmendra Chauhan³, Faris A. Almalki⁴, Hana Mohammed Mujlid⁴

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3685-3711, 2024, DOI:10.32604/cmc.2024.053587 - 12 September 2024

Abstract The mobility and connective capabilities of unmanned aerial vehicles (UAVs) are becoming more and more important in defense, commercial, and research domains. However, their open communication makes UAVs susceptible to undesirable passive attacks such as eavesdropping or jamming. Recently, the inefficiency of traditional cryptography-based techniques has led to the addition of Physical Layer Security (PLS). This study focuses on the advanced PLS method for passive eavesdropping in UAV-aided vehicular environments, proposing a solution to complement the conventional cryptography approach. Initially, we present a performance analysis of first-order secrecy metrics in 6G-enabled UAV systems, namely hybrid… More >

Ftoon H. Kedwan^*, Mohammed Abdur Rahman

Journal on Internet of Things, Vol.6, pp. 43-73, 2024, DOI:10.32604/jiot.2024.052325 - 10 September 2024

Abstract Impressive advancements and novel techniques have been witnessed in AI-based Human Intelligent-Things Interaction (HITI) systems. Several technological breakthroughs have contributed to HITI, such as Internet of Things (IoT), deep and edge learning for deducing intelligence, and 6G for ultra-fast and ultralow-latency communication between cyber-physical HITI systems. However, human-AI teaming presents several challenges that are yet to be addressed, despite the many advancements that have been made towards human-AI teaming. Allowing human stakeholders to understand AI’s decision-making process is a novel challenge. Artificial Intelligence (AI) needs to adopt diversified human understandable features, such as ethics, non-biases,… More >