Multi-Cloud Open Radio Access Network Resource Manager and Orchestrator

Flow Analysis in Heterogeneous Cloud Scenarios

Unified Fog Computing Architecture Integrating O-RAN, MEC, and OneM2M

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.

From Open RAN to Open Spectrum: A Programmable, Intelligent Architecture for Multi-Service Spectrum Coexistence

Considering sharing or coexistence from the perspective of spectrum alone fails to recognize that any spectrum-enabled service also requires (i) radio and processing infrastructure and (ii) a protocol stack, including waveforms and signal processing pipelines. The efficiency of spectrum coexistence frameworks such as Citizen Broadband Radio Service (CBRS) is thus limited to optimizing resource allocation across a single dimension. How to address this limitation, however, remains an open challenge, especially considering the diversity of requirements and operational modes across spectrum services (e.g., sensing, communications, navigation, or positioning). This article introduces Open Spectrum, an architecture that brings softwarization, programmability, and open interfaces to heterogeneous spectrum services, extending the open Radio Access Network (RAN) principles beyond wireless networking. We propose to combine spectrum, services, and infrastructure in a common pool. Its resources are shared and orchestrated by a Spectrum Intelligent Controller (SIC), with plug-and-play spectrum applications, i.e., Spectrum Applications (sApps), and data-driven Radio-Frequency Interference (RFI) modeling using Digital Twins (DTs). We describe the Open Spectrum architecture, shared infrastructure pool, and operational workflows for tenant onboarding and incentives, conflict resolution, and service sharing across sensing, radionavigation, radiolocation, and cellular systems. System-level simulations using the BostonTwin urban DT and Sionna ray tracing show that there exist performance-driven incentives in sharing infrastructure and sharing across multiple services, enabling increased access to spectrum and improvement in median Signal to Interference plus Noise Ratio (SINR) of up to 12 dB.

A Service-Defined Approach for Orchestration of Heterogeneous Applications in Cloud/Edge Platforms

A Service-Defined approach for orchestrating cloud/edge services in a distributed fashion, where each application can define its own orchestration strategy by means of declarative statements, which are parsed into a Service-Defined Orchestrator (SDO).

Next-generation O-RAN Edge: Energy-aware Joint Placement and Migration of Cloud-Native Functions

This paper investigates the energy-aware joint placement and migration of cloud-native functions (CNFs) in an O-RAN edge cloud with a Mixed-Integer Linear Program that minimizes server, transmission, wake-up, and migration energy while satisfying server-resource capacities and one-way delay requirements over the F1 user-plane interface.

Internet of Things-Centric Optimized Service Provisioning in Multi-Cloud Environment

A lightweight, QoS-aware service placement algorithm that evaluates latency, bandwidth, and node load in real time is introduced that yields reduced latency and more consistent wait times relative to heuristic and genetic baselines.