Kanyang Jiang¹, Yingkai Kang², Ming Li^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.083294 - 15 June 2026

Abstract The Internet of Vehicular Agents (IoVA) interconnects distributed AI agents across vehicular networks to deliver real-time intelligent services for vehicular users. Due to the limited computing capacity of vehicles, AI agents are deployed on nearby RoadSide Units (RSUs) to perform computation-intensive inference. As vehicles traverse RSU coverage boundaries, AI agents must migrate to target RSUs to maintain service continuity. However, the communication and computing resources at each RSU are shared among multiple co-served vehicles, creating coupled allocation decisions that jointly determine system latency and energy consumption. To address this challenge, we propose a low-latency and… More >

Qiuguo Guan, Zhiyu Ren^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082704 - 15 June 2026

Abstract To address trust-score drift and unsafe online adaptation under cross-domain attack-contaminated streams in Industrial Internet of Things (IIoT) edge environments, this paper proposes a risk-aware lightweight test-time adaptation (TTA) framework, named RaL-TTA, for dynamic trust evaluation of edge nodes. RaL-TTA constructs a low-dimensional robust feature space and a source-domain normal-entropy reference baseline, and performs selective online maintenance in the target domain through Kolmogorov–Smirnov (KS) drift detection, SafeBrake risk gating, Adaptive Batch Normalization (AdaBN) anchor protection, and budgeted sample-level safeguards. Low-risk batches are adapted by updating only lightweight Batch Normalization (BN) parameters, whereas high-risk batches freeze… More >

Peiying Zhang^1,2, Yihong Yu^1,2, Lizhuang Tan^3,4,*, Shuqing He⁵, Jian Wang⁶, Ameer El-Sayed⁷

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081224 - 15 June 2026

Abstract As a core information infrastructure in the 6G era, the Space-Air-Ground Integrated Network (SAGIN) integrates space-based, air-based, and ground-based network resources to achieve seamless communication across all domains. However, its characteristics such as heterogeneous node coupling and dynamic topology changes make it prone to cascading failures, severely threatening critical business continuity in Internet of Things (IoT) applications spanning smart cities, healthcare, transportation, and industrial automation. This paper conducts systematic research addressing challenges including modeling difficulties in SAGIN cascading failure propagation, insufficient coordination of defense strategies, and poor resource adaptability. First, a multi-factor coupled dynamic model… More >

Ambreen Memon¹, Aaron Bere¹, Muhammad Nadeem Ali², Byung-Seo Kim^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078988 - 15 June 2026

Abstract The modern internet infrastructure has enabled numerous applications by providing a seamless connectivity experience across each mode of connectivity. Infrastructure-based connectivity and device-to-device (D2D) are well-known connectivity modes for internet-based applications. The selection of the underlying communication medium significantly affects energy consumption during data transfer. This study proposes an Energy-Efficient Data Dissemination Approach (EEDDA) that integrates encounter prediction with a multi-criteria decision-making (MCDM) framework to reduce infrastructure-based energy consumption in IoT mobility environments. Unlike traditional optimization approaches that focus on single-objective routing or static network models, the proposed framework dynamically selects between Device-to-Device (D2D) and More >

Devanshi Sharma¹, Umesh Kumar^1,*, Uma Sharma², Isha Pandey¹

Journal on Internet of Things, Vol.8, pp. 155-180, 2026, DOI:10.32604/jiot.2026.080987 - 29 May 2026

Abstract This paper explores the rapidly evolving fields of Robotics and the Internet of Things (IoT), highlighting their key components, technological advancements, levels of autonomy, control systems, and their integration. Robotics contributes to modern industries by enhancing efficiency, precision, and automation. A comprehensive examination is conducted to highlight the convergence of IoT and robotics, particularly their applications in aerospace and other innovative domains, to develop a fundamental understanding of how these systems perform real-time input correction and autonomous decision-making. Additionally, the paper analyzes market trends from 2023 to 2024 and forecasts growth until 2034, emphasizing key More >

Priyanka Halder, Gopikrishnan Sundaram^*

Journal on Internet of Things, Vol.8, pp. 127-153, 2026, DOI:10.32604/jiot.2026.073962 - 29 May 2026

Abstract The need for intelligent learning frameworks that can function under stringent limitations relating to privacy, energy, scalability, and trust has increased due to the Internet of Things’ (IoT) and the Internet of Artificial Things’ (IoAT) explosive expansion. Federated Learning (FL), which allows collaborative model training without sharing raw data, has become a potential approach. Non-IID data delivery, inconsistent client engagement, vulnerability to poisoning assaults, and low resource knowledge are among of the significant obstacles that FL alone must overcome. Blockchain integration adds extra overhead in terms of latency, energy consumption, and scalability, but it has… More >

Oluwatosin Ahmed Amodu¹, Zurina Mohd Hanapi^1,*, Chedia Jarray², Huda Althumali³, Faten A. Saif ⁴, Raja Azlina Raja Mahmood¹, Mohammed Sani Adam⁵, Nor Fadzilah Abdullah⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077054 - 27 May 2026

Abstract Non-terrestrial networks (NTNs)—including UAVs, HAPs, and satellite systems—are rapidly becoming key enablers of wide-area, resilient connectivity for large-scale IoT applications. As these platforms integrate with terrestrial networks to form space–air–ground architectures, optimization challenges related to trajectory, resource management, energy efficiency, and security become increasingly complex. Machine learning (ML) has emerged as a central tool for addressing these challenges by enabling adaptive, data-driven decision-making under uncertainty. This survey presents an optimization-centric review of ML-based NTN-assisted IoT systems focusing on aspect-specific datasets. Using a structured methodology involving dataset curation, keyword filtering, metadata analysis, and citation-based paper selection,… More >

Muhammad Shaheer¹, Feng Zeng^1,*, Aqsa Yasmeen², Mudasir Ahmad Wani^3,*, Kashish Ara Shakil⁴, Muhammad Asim⁵

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079701 - 08 May 2026

Abstract Malware remains a persistent and evolving threat to digital security, highlighting the need for advanced and resilient detection frameworks capable of mitigating increasingly sophisticated and evasive cyberattacks. Although deep learning ensembles have been explored, many existing approaches fail to balance computational efficiency with the diverse feature extraction capabilities needed for complex variants. To address this gap, this study proposes a novel stacking ensemble framework, MalDetect-IoT, which specifically eliminates the requirement for manual feature engineering and domain specific preprocessing traditionally required in malware classification. By fine-tuning two pre-trained models MobileNetV3 for its lightweight efficiency and Xception… More >

Kelan Wang¹, Jianfei Chen^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079644 - 08 May 2026

Abstract As 6G-enabled Industrial Internet of Things (IIoT) evolves, green and sustainable industrial monitoring increasingly relies on edge AI to deliver low-latency diagnosis under tight resource constraints. Industrial cyber–physical systems increasingly rely on heterogeneous sensing and communication infrastructures, where network-side attacks can propagate into physical processes and appear as coupled anomalies. Reliable diagnosis therefore requires joint learning from time-synchronized cyber and physical telemetry rather than modeling them as independent signals. This paper develops Cyber–Physical Symbiosis Network (CPSNet), a model designed for edge-AI deployment with a dual-stream architecture for fixed-window multiclass cross-domain anomaly diagnosis in IIoT. CPSNet… More >

Salahuddin¹, Khalid Haseeb^1,*, Mansoor Nasir¹, NZ Jhanjhi², Mamoona Humayun³

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079584 - 08 May 2026

Abstract Intelligent Transportation System (ITS) interconnects smart technologies for the advancement in communication and autonomous decision making in vehicle interactions. It manages traffic control infrastructure, analyses road conditions, and supports cooperative awareness in a crucial environment. The sensors continuously collect real-time vehicle data, process it, and forward it to analysis servers to predict the behavior of Vehicular Ad hoc Networks (VANETs). Many approaches have been proposed to address research challenges in routing and improve communication for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems. However, due to dynamic topology, the network becomes disturbed and loses established connections, leading… More >