-[6.3 Use Cases \& Frameworks Mapping](#63use-cases--frameworks-mapping)
-[6.3.x](#63x)
-[6.3.x.1 Use Case Driving Deployment](#63x1-use-case-driving-deployment)
-[Table 6.3.x.1-1 – Operational Requirements and Platform Support for Autonomous Vehicle with Continuous Edge Computing](#table-63x1-1--operational-requirements-and-platform-support-for-autonomous-vehicle-with-continuous-edge-computing)
-[6.3.x.1 Use case Driven Deployment](#63x1use-case-driven-deployment)
-[Table 6.3.x.1-1 – Operational Requirements and Platform Support for Smart Warehouse Automation](#table-63x1-1--operational-requirements-and-platform-support-for-smart-warehouse-automation)
-[7 New Internetworking Proposed Recommendations Based on Use Cases](#7new-internetworking-proposed-recommendations-based-on-use-cases)
-[7.1 XXX](#71xxx)
-[Annex A: Title of annex](#annex-a-title-of-annex)
-[Annex B: Title of annex](#annex-b-title-of-annex)
-[B.1 First clause of the annex](#b1-first-clause-of-the-annex)
@@ -170,6 +174,7 @@ All rights reserved.<br />
-[Annex: Bibliography](#annex-bibliography)
-[Annex : Change history](#annex--change-history)
-[History](#history)
-[Document history](#document-history)
<br/>
@@ -249,16 +254,15 @@ For the purposes of the present document, the [following] abbreviations [given i
# 4 Overview
This clause introduces the document, outlining its purpose, scope, and key objectives. It establishes the context of integrating MEC and oneM2M frameworks, highlighting the relevance of Edge and IoT-based technologies in various deployment scenarios. Additionally, it summarizes the key areas explored in the subsequent sections.
The project is focused on three main goals:
This clause introduces the document by outlining its purpose, scope, and key objectives. It sets the foundation for the integration of ETSI MEC and oneM2M frameworks, emphasizing their relevance in enabling advanced Edge and IoT-based deployments across diverse application domains. The document is organized into three main clauses, each addressing a specific aspect of the analysis.
- The ability to deploy the MEC + oneM2M service layers using one or more of the four deployment architectures describes in [the whitepaper]
- Ability to make use of federated learning for training a machine learning model and deploying a trained model.
- Ability to apply machine learning model(s) to a swarm of resources.
Clause 5 presents a domain-oriented analysis of selected use cases, demonstrating how MEC and oneM2M can be effectively applied in practical Edge-IoT scenarios. Use cases are grouped according to relevant domains—such as Mobility, Industrial, and Maritime—to reflect the specific operational context. Within each domain, use cases are described in detail, including the context, involved stakeholders, technical and operational requirements, as well as associated challenges. The role of MEC and oneM2M technologies in addressing these challenges is also examined. These use cases were identified through a structured exploration process involving key stakeholders, who contributed via a dedicated form designed to capture all essential elements of each use case. This approach ensured consistency and completeness by documenting the use case description, actors, requirements, preconditions and postconditions, triggers, and expected interaction flows.
Clause 5 will begin with a representation of use cases ...
Clause 6 will describe the architectures that can support the uses cases defined.
Clause 7 will define the requirements to support the architectures and use cases.
Clause 6 builds on the identified use cases by analyzing the main reference architectures of the MEC and oneM2M frameworks. It highlights their respective core functionalities and explores how they complement each other in supporting Edge-IoT scenarios. The clause also maps architectural elements and capabilities from both frameworks to each use case, identifying existing overlaps and new features that may enhance support for specific scenarios. These mappings serve as the basis for a broader architectural reflection, setting the stage for further technical analysis.
Clause 7 consolidates the insights gained from the architectural mapping by extracting and formalizing new functional and technical recommendations. These recommendations are derived from both common patterns observed across multiple use cases and unique needs emerging from individual scenarios. The resulting output informs the ongoing development of both ETSI MEC and oneM2M, particularly in terms of their interworking and integration. This clause aims to ensure that evolving deployment needs are addressed through well-aligned framework enhancements and targeted standardization efforts.
Overall, the document provides a structured foundation for understanding how MEC and oneM2M can jointly enable scalable, interoperable, and future-oriented Edge-IoT solutions.
# 5 Edge & IoT Domains and Use Cases
@@ -327,8 +331,8 @@ As warehouse operations span large areas, AGVs may move between MEC zones. The M
### 5.3.3 Industrial Digital Twins
T
his use case illustrates the integration of the oneM2M IoT platform with the ETSI MEC edge computing framework to support Industrial Digital Twins (IDTs) in smart manufacturing environments. The goal is to enable continuous monitoring, analysis, and optimization of industrial processes by deploying synchronized digital representations of physical assets across both cloud and edge infrastructures. This approach is fundamental to enabling real-time decision-making, predictive maintenance, and autonomous control in dynamic and distributed industrial settings.
This use case illustrates the integration of the oneM2M IoT platform with the ETSI MEC edge computing framework to support Industrial Digital Twins (IDTs) in smart manufacturing environments. The goal is to enable continuous monitoring, analysis, and optimization of industrial processes by deploying synchronized digital representations of physical assets across both cloud and edge infrastructures. This approach is fundamental to enabling real-time decision-making, predictive maintenance, and autonomous control in dynamic and distributed industrial settings.
The overall system architecture relies on a cloud-based oneM2M IN-CSE (Infrastructure Node Common Service Entity), which functions as a centralized orchestrator and digital repository, and multiple MN-CSEs (Middle Node Common Service Entities) deployed at the edge on MEC nodes physically co-located with manufacturing equipment or microfactories. These edge-based MN-CSEs are responsible for processing time-sensitive data streams such as sensor readings from production lines, robotic cell statuses, energy usage metrics, and environmental conditions with ultra-low latency.
@@ -385,6 +389,7 @@ In this extension, the non-MEC node is realized as a Customer Premises Edge devi
# 6 MEC-oneM2M Architectural & Use Case Mapping
## 6.0 Introduction
This clause provides an analysis of the main reference architectures and characteristics of MEC and oneM2M , highlighting their core functionalities and how they complement each other in the context of Edge-IoT deployments. For each of the identified use cases, the clause maps the relevant architectural elements and functionalities from both, illustrating how they contribute to the scenario. It also identifies potential new features or enhancements that could further support the use case. Where overlapping functionalities exist across use cases, these are acknowledged and will be further analyzed in the following clause 7, which focuses on deriving structured application requirements and identifying gaps for future standardization efforts.
