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  • 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

    ARTICLE

    Multi-Agent Deep Q-Networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

    Prohim Tam1, Sa Math1, Ahyoung Lee2, Seokhoon Kim1,3,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3319-3335, 2022, DOI:10.32604/cmc.2022.023215 - 07 December 2021

    Abstract Federated learning (FL) activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging processes. However, in large-scale heterogeneous Internet of Things (IoT) cellular networks, massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled significantly. This paper introduces the system model of converging software-defined networking (SDN) and network functions virtualization (NFV) to enable device/resource abstractions and provide NFV-enabled edge FL (eFL) aggregation servers for advancing automation and controllability. Multi-agent deep Q-networks (MADQNs) target to enforce a… More >

  • Open Access

    ARTICLE

    Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes

    G. R. Sreekanth1,*, S. Ahmed Najat Ahmed2, Marko Sarac3, Ivana Strumberger3, Nebojsa Bacanin3, Miodrag Zivkovic3

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.020534 - 25 October 2021

    Abstract Fog computing provides quality of service for cloud infrastructure. As the data computation intensifies, edge computing becomes difficult. Therefore, mobile fog computing is used for reducing traffic and the time for data computation in the network. In previous studies, software-defined networking (SDN) and network functions virtualization (NFV) were used separately in edge computing. Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance, reliability, and scalability. SDN/NFV is still in development. The traditional Internet of things (IoT) data analysis system is only based on… More >

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