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  • Open Access

    ARTICLE

    DRL-AMIR: Intelligent Flow Scheduling for Software-Defined Zero Trust Networks

    Wenlong Ke1,2,*, Zilong Li1, Peiyu Chen1, Benfeng Chen1, Jinglin Lv1, Qiang Wang2, Ziyi Jia2, Shigen Shen1

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3305-3319, 2025, DOI:10.32604/cmc.2025.065665 - 03 July 2025

    Abstract Zero Trust Network (ZTN) enhances network security through strict authentication and access control. However, in the ZTN, optimizing flow control to improve the quality of service is still facing challenges. Software Defined Network (SDN) provides solutions through centralized control and dynamic resource allocation, but the existing scheduling methods based on Deep Reinforcement Learning (DRL) are insufficient in terms of convergence speed and dynamic optimization capability. To solve these problems, this paper proposes DRL-AMIR, which is an efficient flow scheduling method for software defined ZTN. This method constructs a flow scheduling optimization model that comprehensively considers… More >

  • Open Access

    ARTICLE

    AI-Integrated Feature Selection of Intrusion Detection for Both SDN and Traditional Network Architectures Using an Improved Crayfish Optimization Algorithm

    Hui Xu, Wei Huang*, Longtan Bai

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3053-3073, 2025, DOI:10.32604/cmc.2025.064930 - 03 July 2025

    Abstract With the birth of Software-Defined Networking (SDN), integration of both SDN and traditional architectures becomes the development trend of computer networks. Network intrusion detection faces challenges in dealing with complex attacks in SDN environments, thus to address the network security issues from the viewpoint of Artificial Intelligence (AI), this paper introduces the Crayfish Optimization Algorithm (COA) to the field of intrusion detection for both SDN and traditional network architectures, and based on the characteristics of the original COA, an Improved Crayfish Optimization Algorithm (ICOA) is proposed by integrating strategies of elite reverse learning, Levy flight,… More >

  • Open Access

    ARTICLE

    Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking

    Abdullah M. Alnajim1,*, Faisal Mohammed Alotaibi2,#, Sheroz Khan3,#

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4515-4535, 2025, DOI:10.32604/cmc.2025.063139 - 19 May 2025

    Abstract Distributed denial of service (DDoS) attacks are common network attacks that primarily target Internet of Things (IoT) devices. They are critical for emerging wireless services, especially for applications with limited latency. DDoS attacks pose significant risks to entrepreneurial businesses, preventing legitimate customers from accessing their websites. These attacks require intelligent analytics before processing service requests. Distributed denial of service (DDoS) attacks exploit vulnerabilities in IoT devices by launching multi-point distributed attacks. These attacks generate massive traffic that overwhelms the victim’s network, disrupting normal operations. The consequences of distributed denial of service (DDoS) attacks are typically… More >

  • Open Access

    ARTICLE

    Metaheuristic-Driven Abnormal Traffic Detection Model for SDN Based on Improved Tyrannosaurus Optimization Algorithm

    Hui Xu, Jiahui Chen*, Zhonghao Hu

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4495-4513, 2025, DOI:10.32604/cmc.2025.062189 - 19 May 2025

    Abstract Nowadays, abnormal traffic detection for Software-Defined Networking (SDN) faces the challenges of large data volume and high dimensionality. Since traditional machine learning-based detection methods have the problem of data redundancy, the Metaheuristic Algorithm (MA) is introduced to select features before machine learning to reduce the dimensionality of data. Since a Tyrannosaurus Optimization Algorithm (TROA) has the advantages of few parameters, simple implementation, and fast convergence, and it shows better results in feature selection, TROA can be applied to abnormal traffic detection for SDN. However, TROA suffers from insufficient global search capability, is easily trapped in… More >

  • Open Access

    ARTICLE

    Priority-Aware Resource Allocation for VNF Deployment in Service Function Chains Based on Graph Reinforcement Learning

    Seyha Ros1,#, Seungwoo Kang1,#, Taikuong Iv1, Inseok Song1, Prohim Tam2, Seokhoon Kim1,3,*

    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 >

  • Open Access

    REVIEW

    A Survey of Link Failure Detection and Recovery in Software-Defined Networks

    Suheib Alhiyari, Siti Hafizah AB Hamid*, Nur Nasuha Daud

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 103-137, 2025, DOI:10.32604/cmc.2024.059050 - 03 January 2025

    Abstract Software-defined networking (SDN) is an innovative paradigm that separates the control and data planes, introducing centralized network control. SDN is increasingly being adopted by Carrier Grade networks, offering enhanced network management capabilities than those of traditional networks. However, because SDN is designed to ensure high-level service availability, it faces additional challenges. One of the most critical challenges is ensuring efficient detection and recovery from link failures in the data plane. Such failures can significantly impact network performance and lead to service outages, making resiliency a key concern for the effective adoption of SDN. Since the More >

  • Open Access

    ARTICLE

    Effective Controller Placement in Software-Defined Internet-of-Things Leveraging Deep Q-Learning (DQL)

    Jehad Ali1,*, Mohammed J. F. Alenazi2

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4015-4032, 2024, DOI:10.32604/cmc.2024.058480 - 19 December 2024

    Abstract The controller is a main component in the Software-Defined Networking (SDN) framework, which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks. In SDN, frequent communication occurs between network switches and the controller, which manages and directs traffic flows. If the controller is not strategically placed within the network, this communication can experience increased delays, negatively affecting network performance. Specifically, an improperly placed controller can lead to higher end-to-end (E2E) delay, as switches must traverse more hops or encounter greater propagation delays when communicating with the controller. This paper introduces… More >

  • Open Access

    ARTICLE

    Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

    Khawaja Tahir Mehmood1,2,*, 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 (Th), maximum available bandwidth (Bd(max)), data transfer (DTransfer), 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 (Bd(max), Th, DTransfer, D(E-E),… More > Graphic Abstract

    Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

  • Open Access

    ARTICLE

    Enhanced Mechanism for Link Failure Rerouting in Software-Defined Exchange Point Networks

    Abdijalil Abdullahi1,2, Selvakumar Manickam2,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4361-4385, 2024, DOI:10.32604/cmc.2024.054215 - 12 September 2024

    Abstract Internet Exchange Point (IXP) is a system that increases network bandwidth performance. Internet exchange points facilitate interconnection among network providers, including Internet Service Providers (ISPs) and Content Delivery Providers (CDNs). To improve service management, Internet exchange point providers have adopted the Software Defined Network (SDN) paradigm. This implementation is known as a Software-Defined Exchange Point (SDX). It improves network providers’ operations and management. However, performance issues still exist, particularly with multi-hop topologies. These issues include switch memory costs, packet processing latency, and link failure recovery delays. The paper proposes Enhanced Link Failure Rerouting (ELFR), an… More >

  • Open Access

    ARTICLE

    Network Traffic Synthesis and Simulation Framework for Cybersecurity Exercise Systems

    Dong-Wook Kim1, Gun-Yoon Sin2, Kwangsoo Kim3, Jaesik Kang3, Sun-Young Im3, Myung-Mook Han1,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3637-3653, 2024, DOI:10.32604/cmc.2024.054108 - 12 September 2024

    Abstract In the rapidly evolving field of cybersecurity, the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly critical. Traditional methods often fall short in capturing the dynamic and complex nature of modern cyber threats. To address this gap, we propose a comprehensive framework designed to create authentic network environments tailored for cybersecurity exercise systems. Our framework leverages advanced simulation techniques to generate scenarios that mirror actual network conditions faced by professionals in the field. The cornerstone of our approach is the use of a conditional tabular generative adversarial network (CTGAN),… More >

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