Xuehan Li¹, Tao Jing², Yang Wang², Bo Gao³, Jing Ai⁴, Minghao Zhu^5,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075426 - 12 March 2026

Abstract With the deep integration of cloud computing, edge computing and the Internet of Things (IoT) technologies, smart manufacturing systems are undergoing profound changes. Over the past ten years, an extensive body of research on cloud-edge-end systems has been generated. However, challenges such as heterogeneous data fusion, real-time processing and system optimization still exist, and there is a lack of systematic review studies. In this paper, we review a cloud-edge-end collaborative sensing-communication-computing-control (SC3) system. This system integrates four layers of sensing, communication, computing and control to address the complex challenges of real-time decision making, resource… More >

Yujie Tian¹, Ming Zhu¹, Jing Li^1,*, Cong Liu², Ziyang Zhang¹

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075063 - 12 March 2026

Abstract Workflow scheduling is critical for efficient cloud resource management. This paper proposes Tunicate Swarm-Highest Response Ratio Next, a novel scheduler that synergistically combines the Tunicate Swarm Algorithm with the Highest Response Ratio Next policy. The Tunicate Swarm Algorithm generates a cost-minimizing task-to-VM mapping scheme, while the Highest Response Ratio Next dynamically dispatches tasks in the ready queue with the highest-priority. Experimental results demonstrate that the Tunicate Swarm-Highest Response Ratio Next reduces costs by up to 94.8% compared to meta-heuristic baselines. It also achieves competitive cost efficiency vs. a learning-based method while offering superior operational simplicity More >

Qian Zhang¹, Lei Fu^1,2, Renzhou Chen³, Xu Zhan^4,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074939 - 12 March 2026

Abstract Triply periodic minimal surface (TPMS) structures are widely utilized in engineering and biomedical fields owing to their superior mechanical and functional properties. However, limited by the current additive manufacturing (AM) techniques, insufficient wall thickness often leads to poor forming quality or even printing failure. Therefore, accurate prediction of wall thickness parameters during the design stage is essential. This study proposes a prediction approach for the wall thickness parameters of TPMS models by integrating a Convolutional Neural Network–Support Vector Regression (CNN-SVM) framework with Multiple Linear Regression (MLR). A total of 152 TPMS models were randomly generated,… More >

Jinwei Mao^1,2, Wang Luo^1,2,*, Jiangtao Xu³, Daohua Zhu³, Wei Liang³, Zhechen Huang³, Bao Feng^1,2, Shuang Yang^1,2

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.072505 - 12 March 2026

Abstract With the rapid development of power Internet of Things (IoT) scenarios such as smart factories and smart homes, numerous intelligent terminal devices and real-time interactive applications impose higher demands on computing latency and resource supply efficiency. Multi-access edge computing technology deploys cloud computing capabilities at the network edge; constructs distributed computing nodes and multi-access systems and offers infrastructure support for services with low latency and high reliability. Existing research relies on a strong assumption that the environmental state is fully observable and fails to thoroughly consider the continuous time-varying features of edge server load fluctuations,… More >

Josmell Alva Alcántara¹, Elder Mendoza Orbegoso¹, Nattan Roberto Caetano², Luis Julca Verástegui¹, Juan Bengoa Seminario¹, Jimmy Silvera Otañe¹, Yvan Leiva Calvanapón¹, Giulio Lorenzini^3,*

Frontiers in Heat and Mass Transfer, Vol.24, No.1, 2026, DOI:10.32604/fhmt.2025.074995 - 28 February 2026

Abstract The continuous improvement of solar thermal technologies is essential to meet the growing demand for sustainable heat generation and to support global decarbonization efforts. This study presents the design, implementation, and validation of a real-time monitoring framework based on the Internet of Things (IoT) and cloud computing to enhance the thermal performance of evacuated tube solar water heaters (ETSWHs). A commercial system and a custom-built prototype were instrumented with Industry 4.0 technologies, including platinum resistance temperature detectors (PT100), solar irradiance and wind speed sensors, a programmable logic controller (PLC), a SCADA interface, and a cloud-connected… More >

Mangala Natampalli^1,2,*, Kruthika Gottikere Channagangaiah³, Bodi Eswara Reddy¹, Rajkumar Buyya⁴, Venugopal Kupanna Rajuk³, Sundaraja Sitharama Iyengar⁵, Lalit Mohan Patnaik⁶

Journal on Internet of Things, Vol.8, pp. 1-30, 2026, DOI:10.32604/jiot.2026.067726 - 24 February 2026

Abstract Contemporary banking focuses on self-service and customer-centric experience by harnessing Internet of Things (IoT) and Cloud Computing. However, these systems remain vulnerable to multifaceted cyberattacks. The IoT-Cloud-based systems can be safeguarded through authentication, confidentiality, integrity, availability, privacy, and non-repudiation. This work proposes a multi-stage security consisting of Generative Adversarial Networks (GAN) for facial authentication, hybrid Curvelet and Least-Significant-Bit (LSB) Steganography for data protection, and Ethereum Blockchain for transactions and storage security to provide complete protection to the self-service pipeline. Customers are authenticated using live images from IoT cameras by GAN facial recognition. Improved data concealment… More >

Aman Aman Ullah^1,2,#, Yanfeng Wu^1,#, Shaheryar Najam³, Nouf Abdullah Almujally⁴, Ahmad Jalal^5,6,*, Hui Liu^1,7,8,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072508 - 10 February 2026

Abstract Human object detection and recognition is essential for elderly monitoring and assisted living however, models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings. To address this, we present SCENET-3D, a transformer-driven multimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline. In the first stage, scene analysis, rich geometric and texture descriptors are extracted from RGB frames, including surface-normal histograms, angles between neighboring normals, Zernike moments, directional standard deviation, and Gabor-filter responses. In the second stage, scene-object analysis, non-human objects… More >

Md. Al-Hasan¹, Mst. Rubina Aktar², Fahmid Al Farid^3,4,*, Md. Shamim Anower⁵, Abu Saleh Musa Miah^1,6, Md. Hezerul Abdul Karim^4,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.071280 - 10 February 2026

Abstract The rapid growth in available network bandwidth has directly contributed to an exponential increase in mobile data traffic, creating significant challenges for network energy consumption. Also, with the extraordinary growth of mobile communications, the data traffic has dramatically expanded, which has led to massive grid power consumption and incurred high operating expenditure (OPEX). However, the majority of current network designs struggle to efficiently manage a massive amount of data using little power, which degrades energy efficiency performance. Thereby, it is necessary to have an efficient mechanism to reduce power consumption when processing large amounts of… More >

Han-Yu Lin, Tung-Tso Tsai^*, Yi-Chuan Wang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073234 - 12 January 2026

Abstract Cloud services, favored by many enterprises due to their high flexibility and easy operation, are widely used for data storage and processing. However, the high latency, together with transmission overheads of the cloud architecture, makes it difficult to quickly respond to the demands of IoT applications and local computation. To make up for these deficiencies in the cloud, fog computing has emerged as a critical role in the IoT applications. It decentralizes the computing power to various lower nodes close to data sources, so as to achieve the goal of low latency and distributed processing.… More >

Ahmed Awad Mohamed¹, Eslam Abdelhakim Seyam^2,*, Ahmed R. Elsaeed³, Laith Abualigah⁴, Aseel Smerat^5,6, Ahmed M. AbdelMouty⁷, Hosam E. Refaat⁸

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073171 - 12 January 2026

Abstract In recent years, fog computing has become an important environment for dealing with the Internet of Things. Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing. Task scheduling is crucial for efficiently handling IoT user requests, thereby improving system performance, cost, and energy consumption across nodes in cloud computing. With the large amount of data and user requests, achieving the optimal solution to the task scheduling problem is challenging, particularly in terms of cost and energy efficiency. In this paper, we develop novel strategies to save energy consumption across… More >