Lincong Zhang¹, Yuqing Liu¹, Kefeng Wei², Weinan Zhao¹, Bo Qian^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.069108 - 10 November 2025

Abstract In the field of edge computing, achieving low-latency computational task offloading with limited resources is a critical research challenge, particularly in resource-constrained and latency-sensitive vehicular network environments where rapid response is mandatory for safety-critical applications. In scenarios where edge servers are sparsely deployed, the lack of coordination and information sharing often leads to load imbalance, thereby increasing system latency. Furthermore, in regions without edge server coverage, tasks must be processed locally, which further exacerbates latency issues. To address these challenges, we propose a novel and efficient Deep Reinforcement Learning (DRL)-based approach aimed at minimizing average… More >

Kunpeng Zhou¹, Tao Wu^1,*, Jia Zhang²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-27, 2026, DOI:10.32604/cmc.2025.068160 - 10 November 2025

Abstract Over the past few years, video live streaming has gained immense popularity as a leading internet application. In current solutions offered by cloud service providers, the Group of Pictures (GOP) length of the video source often significantly impacts end-to-end (E2E) latency. However, designing an optimized GOP structure to reduce this effect remains a significant challenge. This paper presents two key contributions. First, it explores how the GOP length at the video source influences E2E latency in mainstream cloud streaming services. Experimental results reveal that the mean E2E latency increases linearly with longer GOP lengths. Second, More >

Khawaja Tahir Mehmood^1,*, 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 >

Fang-Yie Leu¹, Kun-Lin Tsai^2,*, Li-Woei Chen³, Deng-Yao Yao², Jian-Fu Tsai², Ju-Wei Zhu², Guo-Wei Wang²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1937-1957, 2025, DOI:10.32604/cmc.2025.068486 - 29 August 2025

Abstract With the rapid development of Cloud-Edge-End (CEE) computing, the demand for secure and lightweight communication protocols is increasingly critical, particularly for latency-sensitive applications such as smart manufacturing, healthcare, and real-time monitoring. While traditional cryptographic schemes offer robust protection, they often impose excessive computational and energy overhead, rendering them unsuitable for use in resource-constrained edge and end devices. To address these challenges, in this paper, we propose a novel lightweight encryption framework, namely Dynamic Session Key Allocation with Time-Indexed Ascon (DSKA-TIA). Built upon the NIST-endorsed Ascon algorithm, the DSKA-TIA introduces a time-indexed session key generation mechanism… More >

P. William^1,2, Ved Prakash Mishra¹, Osamah Ibrahim Khalaf^3,*, Arvind Mukundan⁴, Yogeesh N⁵, Riya Karmakar⁶

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5133-5156, 2025, DOI:10.32604/cmc.2025.065840 - 30 July 2025

Abstract Cloud computing has become an essential technology for the management and processing of large datasets, offering scalability, high availability, and fault tolerance. However, optimizing data replication across multiple data centers poses a significant challenge, especially when balancing opposing goals such as latency, storage costs, energy consumption, and network efficiency. This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization (DMGO), designed to enhance data replication efficiency in cloud environments. Unlike traditional static replication systems, DMGO adapts dynamically to variations in network conditions, system demand, and resource availability. The approach utilizes multi-objective optimization More >

Reem Alkanhel^1,#, Abuzar B. M. Adam^2,#, Samia Allaoua Chelloug¹, Dina S. M. Hassan^1,*, Mohammed Saleh Ali Muthanna³, Ammar Muthanna⁴

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 607-624, 2025, DOI:10.32604/cmc.2025.063206 - 09 June 2025

Abstract The 3GPP standard defines the requirements for next-generation wireless networks, with particular attention to Ultra-Reliable Low-Latency Communications (URLLC), critical for applications such as Unmanned Aerial Vehicles (UAVs). In this context, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technique to improve spectrum efficiency and user fairness by allowing multiple users to share the same frequency resources. However, optimizing key parameters–such as beamforming, rate allocation, and UAV trajectory–presents significant challenges due to the nonconvex nature of the problem, especially under stringent URLLC constraints. This paper proposes an advanced deep learning-driven approach to address the resulting… 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 >

Woongkyu Park¹, Yeongyu Choi², Mahammad Shareef Mekala³, Gyu Sang Choi¹, Kook-Yeol Yoo¹, Ho-youl Jung^1,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3965-3981, 2025, DOI:10.32604/cmc.2025.059966 - 06 March 2025

Abstract Designing fast and accurate neural networks is becoming essential in various vision tasks. Recently, the use of attention mechanisms has increased, aimed at enhancing the vision task performance by selectively focusing on relevant parts of the input. In this paper, we concentrate on squeeze-and-excitation (SE)-based channel attention, considering the trade-off between latency and accuracy. We propose a variation of the SE module, called squeeze-and-excitation with layer normalization (SELN), in which layer normalization (LN) replaces the sigmoid activation function. This approach reduces the vanishing gradient problem while enhancing feature diversity and discriminability of channel attention. In… More >

Ibrar Afzal¹, Noor ul Amin^1,*, Zulfiqar Ahmad^1,*, Abdulmohsen Algarni²

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1377-1399, 2025, DOI:10.32604/cmc.2024.057755 - 03 January 2025

Abstract The deployment of the Internet of Things (IoT) with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses, smart cities, and smart transportation systems. Fog computing tackles a range of challenges, including processing, storage, bandwidth, latency, and reliability, by locally distributing secure information through end nodes. Consisting of endpoints, fog nodes, and back-end cloud infrastructure, it provides advanced capabilities beyond traditional cloud computing. In smart environments, particularly within smart city transportation systems, the abundance of devices and nodes poses significant challenges related… More >

Khawaja Tahir Mehmood^1,2,*, Shahid Atiq¹, Intisar Ali Sajjad³, Muhammad Majid Hussain⁴, Malik M. Abdul Basit²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1673-1708, 2024, DOI:10.32604/cmes.2024.053903 - 27 September 2024

Abstract Software-Defined Networking (SDN), with segregated data and control planes, provides faster data routing, stability, and enhanced quality metrics, such as throughput (T_h), maximum available bandwidth (B_d(max)), data transfer (D_Transfer), and reduction in end-to-end delay (D_(E-E)). This paper explores the critical work of deploying SDN in large­scale Data Center Networks (DCNs) to enhance its Quality of Service (QoS) parameters, using logically distributed control configurations. There is a noticeable increase in Delay_(E-E) when adopting SDN with a unified (single) control structure in big DCNs to handle Hypertext Transfer Protocol (HTTP) requests causing a reduction in network quality parameters (B_d(max), T_h, D_Transfer, D_(E-E),… More > Graphic Abstract