Jul 2026· International Conference on Computer Communications and Networks· pp. 1-6· 0 citations· 28 references
Abstract
As 5G and Beyond networks increasingly expose programmable capabilities to vertical industries through standardized APIs such as CAMARA, new challenges emerge regarding efficient and reliable resource orchestration. In this paper we present a vertical-aware orchestration framework based on intelligent edge-deployed network applications that enable real-time coordination between vertical services and the 5G network. We introduce the Quality Awareness EdgeApp, a context-aware solution for dynamic per-UE QoS adaptation using exposed network APIs. The proposed framework is validated in a real-world 5G Standalone deployment at the Port of Antwerp-Bruges (Belgium) for teleoperated vessel operations. Our experimental results demonstrate improved SLA adherence and resource efficiency compared to static slicing and overprovisioning approaches. Our proposed architecture represents a practical step toward adaptive and scalable orchestration for 5G and Beyond vertical services.
An agentic OP framework autonomously reconciles stringent Service Level Agreements (SLAs) while enhancing infrastructure energy efficiency and establishing a scalable blueprint for cross-domain Network-as-a-Service (NaaS) models that align standardised exposure with 6G autonomous requirements.
METIS is a declarative slice orchestrator that manages the Day-0/1/2 lifecycle of network slice instances through cascaded reconciliation loops, and derives 3GPP-aligned slice profiles via hierarchical aggregation following the 5G quality-of-service model.
Arman Divband, A. Yaghoubian, Navid Nikaein· arXiv.org· 0 citations
A compact reasoning model trained with verifier-based self-verification and periodically refined online via shadow updates is deployed, showing manageable, near-linear control-plane overhead as domains scale and during domain joins, and robust decision quality, including recovery after objective changes.
Masoud Shokrnezhad, T. Taleb· IEEE Network· 0 citations
This paper proposes an innovative solution using AI-based microservices architecture in combination with .NET and Azure technologies. The architecture is aimed at developing flexible enterprise applications by means of implementing elastic orchestration. In this regard, the novel architecture of Elastic Cognitive Orchestration Network (ECONet) has been proposed in which adaptive service orchestration along with intelligent load-balancing capabilities have been integrated into one solution in order to achieve fault tolerance and elasticity. It can be concluded from the experimental analysis that the proposed architecture achieves accuracy equal to 96.2%. ECONet provides a significant step forward in enterprise cloud systems design, integrating intelligence right into orchestration to cut down delays and make the system more adaptable. With its flexibility in terms of being able to seamlessly integrate with both .NET and Azure, the architecture is guaranteed to fit well within existing enterprise setups and can be deployed easily. Using AI-based orchestration allows for lower overhead and increased resilience of the system under changing load conditions. ECONet's proven 96.2% accuracy confirms its reliability in terms of efficiency and automation.
Amit Makwana· 2026 7th International Confe...· 0 citations
This paper presents a comprehensive study of edge-cloud orchestration strategies tailored for scalable industrial automation systems, and reveals that intelligent orchestration can significantly enhance operational efficiency, system scalability, and responsiveness in industrial settings.
A. Reza· International Journal of Mac...· 0 citations
Heterogeneous multi-UAV fleets act as highly dynamic mobile Internet of Things (IoT) nodes, but they often integrate platforms with incompatible telemetry and control semantics, hindering safe and scalable coordination. This paper presents an Asset Administration Shell (AAS)-driven digital twin architecture for the cloud continuum that decouples protocol translation from mission orchestration, pushing compute power closer to the edge. The first contribution of this work is a four-layer communication model mapped across the IoT and edge continuum, spanning physical-digital synchronization at the network edge, inter-digital-twin interaction, digitaltwin/GCS supervision in the fog/cloud layer, and a safety-critical physical/GCS bypass. The second contribution is a UAV AAS submodel that standardizes runtime state, energy, payload, and wireless QoS descriptors. The third contribution is an analytical validation framework based on bounded digital-twin staleness $\left(\Delta S_{\max }=30 ~\text{ms}\right)$ to evaluate semantic task reallocation and QoS-aware telemetry adaptation. At a representative cruise speed of 15 m/s, the worst-case position uncertainty induced by semantic latency is 0.45 m, which is acceptable for highlevel mission handoff. For degraded links, stability conditions are derived for queue-bounded latest-state forwarding and hysteresis-based telemetry control. The analysis indicates that AAS enables protocol-agnostic interoperability while preserving orchestration timeliness.
M. Bampi, P. H. M. Pereira, E. P. de Freitas· International Conference on...· 0 citations
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