Jul 2026· International Conference on Computer Communications and Networks· pp. 1-2· 0 citations· 6 references
Abstract
Fifth-generation (5G) networks and the Internet of Things (IoT) demand unprecedented levels of scalability and ultra-low latency. Addressing these needs requires not only advanced radio technologies but also a cohesive integration of diverse architectural standards. In this paper, we present a unified fog computing framework inspired by ETSI and OneM2M technical literature that merges the Open Radio Access Network (O-RAN) architecture, Multi-Access Edge Computing (MEC), and the OneM2M IoT standard. This approach enables real-time resource allocation, reduces end-to-end latency, alleviates network congestion, and streamlines interoperability across heterogeneous deployments. Through a simulated testbed, we demonstrate how MEC and OneM2M elements can use near-RT RIC intel to optimize service delivery. The results highlight the feasibility and potential performance gains of an integrated O-RAN-MEC-OneM2M environment, paving the way for more robust, scalable, and efficient 5G IoT solutions.
The study concludes that intelligent edge computing architectures will play a vital role in supporting future real-time applications and next-generation 6G-enabled digital ecosystems.
Alan Bundy· International Journal of Mod...· 0 citations
This work introduces an emulation framework that allows developers and operators to decide how to deploy networks, computing devices, and applications in a Computing Continuum environment, ensuring compliance with established Quality of Service standards.
José Gómez-delaHiz, J. Herrera, S. Laso et al.· Infocommunications journal· 0 citations
The proposed IoTScal-CoM middleware employs only native oneM2M capabilities such as RTT, packet loss rate, CPU, and memory usage in order to guarantee the SLA conformity without changing the main standard specifications.
S. Abourriche, A. Zyane, A. Ghammaz· EPJ Web of Conferences· 1 citation
Intent-Based Networking (IBN) has emerged as a promising paradigm for simplifying network management by allowing operators and applications to specify high-level service objectives rather than low-level device configurations. Early IBN research was mainly developed in Software-Defined Networking (SDN), Network Function Virtualization (NFV), transport networks, core networks, and data-center environments, where programmability, virtualization, and relatively stable infrastructure models enabled intent translation, orchestration, and assurance. However, realizing IBN in end-to-end mobile networks is more challenging because the Radio Access Network (RAN) is highly dynamic, wireless-channeldependent, mobility-sensitive, and governed by multiple control timescales. The emergence of Open RAN (O-RAN) changes this landscape by making the RAN programmable, disaggregated, data-driven, and control-lable through non-real-time and near-real-time intelligent control loops. This survey reviews the evolution of IBN from SDN/NFV-enabled automation toward O-RAN-driven end-to-end intent-based networking for 5G-Advanced and 6G. We discuss architectural mechanisms, key challenges, recent advances in AI-driven and agentic IBN, and future research directions including Large Language Model (LLM)-based intent translation, contractbased O-RAN slicing, digital twin-assisted validation, and trustworthy closed-loop orchestration.
Dongwook Won, Thanh Thien-An Dang, Ton That Tam Dinh et al.· International Conference on...· 0 citations
The results of the analysis indicate that 6G can contribute to a substantial improvement of IoT performance in smart cities, healthcare, industrial automation and control applications (manufacturing science), autonomous transportation and precision agriculture.
Md Asaduzaman, Ferdous Hossain, T. Geok· International Journal of Ele...· 0 citations
This review explores the recent approaches of the state of the art focused on service orchestration in IoT edge-cloud environments, concentrating on architectures and methodologies that enable resource allocation and service management.
Claudio Marche· IEEE Access· 0 citations
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