Yu-Xiang Zhao^*, Yi Lee

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 791-810, 2025, DOI:10.32604/cmc.2025.065048 - 09 June 2025

Abstract Bird species classification is not only a challenging topic in artificial intelligence but also a domain closely related to environmental protection and ecological research. Additionally, performing edge computing on low-level devices using small neural networks can be an important research direction. In this paper, we use the EfficientNetV2B0 model for bird species classification, applying transfer learning on a dataset of 525 bird species. We also employ the BiRefNet model to remove backgrounds from images in the training set. The generated background-removed images are mixed with the original training set as a form of data augmentation.… More >

Mohammad Tabrez Quasim^1,*, 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 >

Seo Yeon Moon¹, Byung Hyun Jo¹, Abir El Azzaoui¹, Sushil Kumar Singh², Jong Hyuk Park^1,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 25-55, 2025, DOI:10.32604/cmc.2025.062966 - 09 June 2025

Abstract With the rapid advancement of ICT and IoT technologies, the integration of Edge and Fog Computing has become essential to meet the increasing demands for real-time data processing and network efficiency. However, these technologies face critical security challenges, exacerbated by the emergence of quantum computing, which threatens traditional encryption methods. The rise in cyber-attacks targeting IoT and Edge/Fog networks underscores the need for robust, quantum-resistant security solutions. To address these challenges, researchers are focusing on Quantum Key Distribution and Post-Quantum Cryptography, which utilize quantum-resistant algorithms and the principles of quantum mechanics to ensure data confidentiality More >

Zhipeng Qin^1,2,*, Hanbing Yan³, Biyang Zhang², Peng Wang², Yitao Li³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5811-5829, 2025, DOI:10.32604/cmc.2025.063308 - 19 May 2025

Abstract With the widespread adoption of encrypted Domain Name System (DNS) technologies such as DNS over Hyper Text Transfer Protocol Secure (HTTPS), traditional port and protocol-based traffic analysis methods have become ineffective. Although encrypted DNS enhances user privacy protection, it also provides concealed communication channels for malicious software, compelling detection technologies to shift towards statistical feature-based and machine learning approaches. However, these methods still face challenges in real-time performance and privacy protection. This paper proposes a real-time identification technology for encrypted DNS traffic with privacy protection. Firstly, a hierarchical architecture of cloud-edge-end collaboration is designed, incorporating More >

Sreebha Bhaskaran^*, Supriya Muthuraman

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5037-5070, 2025, DOI:10.32604/cmc.2025.062657 - 19 May 2025

Abstract Efficient resource provisioning, allocation, and computation offloading are critical to realizing low-latency, scalable, and energy-efficient applications in cloud, fog, and edge computing. Despite its importance, integrating Software Defined Networks (SDN) for enhancing resource orchestration, task scheduling, and traffic management remains a relatively underexplored area with significant innovation potential. This paper provides a comprehensive review of existing mechanisms, categorizing resource provisioning approaches into static, dynamic, and user-centric models, while examining applications across domains such as IoT, healthcare, and autonomous systems. The survey highlights challenges such as scalability, interoperability, and security in managing dynamic and heterogeneous infrastructures. More >

Khulud Salem Alshudukhi¹, Mamoona Humayun^2,*, Ghadah Naif Alwakid¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1973-1986, 2025, DOI:10.32604/cmc.2025.063077 - 16 April 2025

Abstract The Internet of Things (IoT) and edge computing have substantially contributed to the development and growth of smart cities. It handled time-constrained services and mobile devices to capture the observing environment for surveillance applications. These systems are composed of wireless cameras, digital devices, and tiny sensors to facilitate the operations of crucial healthcare services. Recently, many interactive applications have been proposed, including integrating intelligent systems to handle data processing and enable dynamic communication functionalities for crucial IoT services. Nonetheless, most solutions lack optimizing relaying methods and impose excessive overheads for maintaining devices’ connectivity. Alternatively, data More >

Seyha Ros^1,#, Seungwoo Kang^1,#, Taikuong Iv¹, Inseok Song¹, Prohim Tam², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1649-1665, 2025, DOI:10.32604/cmc.2025.062716 - 16 April 2025

Abstract Recently, Network Functions Virtualization (NFV) has become a critical resource for optimizing capability utilization in the 5G/B5G era. NFV decomposes the network resource paradigm, demonstrating the efficient utilization of Network Functions (NFs) to enable configurable service priorities and resource demands. Telecommunications Service Providers (TSPs) face challenges in network utilization, as the vast amounts of data generated by the Internet of Things (IoT) overwhelm existing infrastructures. IoT applications, which generate massive volumes of diverse data and require real-time communication, contribute to bottlenecks and congestion. In this context, Multi-access Edge Computing (MEC) is employed to support resource… More >

Cui Zhang¹, Maoxin Ji², Qiong Wu^2,*, Pingyi Fan³, Qiang Fan⁴

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3519-3536, 2025, DOI:10.32604/cmc.2025.061292 - 16 April 2025

Abstract As Internet of Vehicles (IoV) technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to malicious external attacks, resulting in information loss or even tampering, thereby creating serious security vulnerabilities. Blockchain technology can maintain a shared ledger among servers. In the Raft consensus mechanism, as long as more than half of the nodes remain operational, the system will not collapse, effectively maintaining the system’s robustness and security. To protect vehicle information, we propose a… More >

Jun Li^1,*, Yawei Dong¹, Liang Ni¹, Guopeng Feng¹, Fangfang Shan^1,2

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3537-3552, 2025, DOI:10.32604/cmc.2025.059325 - 16 April 2025

Abstract With the development of vehicle networks and the construction of roadside units, Vehicular Ad Hoc Networks (VANETs) are increasingly promoting cooperative computing patterns among vehicles. Vehicular edge computing (VEC) offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure, thereby reducing the computational burden on connected vehicles. However, this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation nodes. Existing vehicular edge computing platforms have not adequately considered the misbehavior of vehicles. We propose a practical task offloading algorithm based on reputation assessment to More >

Aishwarya Rajasekar^*, Vetriselvi Vetrian

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 225-254, 2025, DOI:10.32604/cmes.2025.062642 - 11 April 2025

Abstract The integration of technologies like artificial intelligence, 6G, and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle applications. However, these advancements also generate a surge in data processing requirements, necessitating the offloading of vehicular tasks to edge servers due to the limited computational capacity of vehicles. Despite recent advancements, the robustness and scalability of the existing approaches with respect to the number of vehicles and edge servers and their resources, as well as privacy, remain a concern. In this paper, a lightweight… More >