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6.1 Architecture for oneM2M and MEC

Clause 5.1 describes the four deployment options for oneM2M and MEC integration. These options range from deploying oneM2M in a cloud platform with MEC at the edge (Option A) to tightly coupling oneM2M and MEC within the same edge node (Option D). Each option presents different technical and business implications, with varying degrees of integration and performance benefits.

Four architectures

This clause looks at each of the deployments and identifies the unique components involved in integration of oneM2M and ETSI MEC. These 4 deployment options are reflected in the following diagram with components that are needed to implement each deployment. This clause will identify the components and then solutions that are needed to be implemented will be described in clause 7.

6.1.1 ETSI MEC IPE

Define a MEC Interworking Proxy Entity (IPE) that acts as a bridge between the MEC and oneM2M environments, facilitating seamless communication and data exchange. The MEC IPE may deployed as a MEC application that is hosted on the MEC platform or some other platform.

  • The MEC IPE will follow existing oneM2M IPE (TS-0033 IPE) principles to convert data that comes from devices that use the MEC APIs to a oneM2M resource structure.
  • The MEC IPE will operate as a MEC application and register to the MEC platform.
  • The MEC IPE will support the discovery of MEC services and capabilities exposed by the MEC platform.
  • The MEC IPE may discover and provision devices that are connected to the MEC platform.

This is shown in deployment option A and B.

6.1.2 3rd Party IPE

Define a 3rd Party Interworking Proxy Entity (IPE) that allows external applications or services to interact with the oneM2M and MEC environments. This IPE can be used to extend the capabilities of the MEC platform by integrating with external systems. - The 3rd Party IPE will follow existing oneM2M IPE (TS-0033 IPE) principles to convert data that comes from external applications to a oneM2M resource structure. - The 3rd Party IPE will operate as a MEC application and register to the MEC platform. - The 3rd Party IPE may also provide additional functionality, such as data aggregation or analytics, to leverage the capabilities of the MEC platform.

This is shown in deployment option A.

6.1.3 Mca Proxy

Define a Mca Proxy that enables communication between oneM2M devices and the registered CSE. This component is needed to facilitate communication between oneM2M devices where there is no direct connection to the IN-CSE. In the oneM2M architecture devices communicate with CSEs using the Mca reference point, however devices cannot directly communicate with other oneM2M applications or devices. A new component is needed to facilitate this communication. - The Mca Proxy is implemented as an MEC Application. - The Mca Proxy will facilitate communication between oneM2M devices and the registered CSE by acting as an intermediary. - The Mca Proxy may also provide additional functionality, such as security processing or provisioning.

This is shown in deployment option A.

6.1.4 Swarm Compute AE

Define a Swarm Compute Application Entity (AE) that enables swarm computing capabilities within the oneM2M and MEC environments. This AE will facilitate the coordination and management of multiple devices working together to perform complex tasks. - The Swarm Compute AE will be implemented as a MEC application and register to the MEC platform. - The Swarm Compute AE will support the orchestration and management of swarm computing tasks across multiple devices. - The Swarm Compute AE will leverage MEC services and capabilities to enhance the performance and efficiency of swarm computing operations.

This is shown in deployment option B.

6.1.5 Federated Learning AE

Define a Federated Learning Application Entity (AE) that enables federated learning capabilities within the oneM2M and MEC environments. This AE will facilitate the coordination and management of multiple devices working together to perform distributed machine learning tasks. - The Federated Learning AE will be implemented as a MEC application and register to the MEC platform. - The Federated Learning AE will support the orchestration and management of federated learning tasks across multiple devices. - The Federated Learning AE will leverage MEC services and capabilities to enhance the performance and efficiency of federated learning operations.

This is shown in deployment option B.

6.1.6 3rd Party IPE MN-AE

Define a 3rd Party IPE (MN-AE) that acts as an intermediary between non-oneM2M devices and the oneM2M architecture. This IPE will facilitate the interaction between non-oneM2M devices and oneM2M applications by converting data formats and managing communication protocols. The difference between the 3rd Party IPE (MN-AE) and the 3rd Party IPE (MEC APP) is that it is not managed by the MEC platform. (see 6.1.4) - The 3rd Party IPE (MN-AE) will follow existing oneM2M IPE (TS-0033 IPE) principles to convert data that comes from non-oneM2M devices to a oneM2M resource structure. - The 3rd Party IPE (MN-AE) will register to the MEC platform. - The 3rd Party IPE (MN-AE) will support the discovery of services and capabilities exposed by the MEC platform.

This is shown in deployment option B.

6.1.7 MEC CSF

Define a MEC Common Service Framework (CSF) that provides a set of common services and APIs for MEC applications. The MEC CSF will enable seamless integration and interoperability between MEC applications and oneM2M services. - The MEC CSF will be registered to the MEC platform. - The MEC CSF will leverage MEC services and capabilities to enhance the performance and efficiency of registered devices. - The MEC CSF will provide a unified API for oneM2M applications to access MEC services.

This is shown in deployment option C.

6.1.8 Swarm Computing CSF

Define a Swarm Computing Common Service Framework (CSF) that provides a set of common services and APIs for swarm computing applications. The Swarm Computing CSF will enable seamless integration and interoperability between swarm computing applications and oneM2M services. - The Swarm Computing CSF will provide a unified API for oneM2M applications to access swarm computing services.

This is shown in deployment option D.

6.1.9 Federated Learning CSF

Define a Federated Learning Common Service Framework (CSF) that provides a set of common services and APIs for federated learning applications. The Federated Learning CSF will enable seamless integration and interoperability between federated learning applications and oneM2M services. - The Federated Learning CSF will provide a unified API for oneM2M applications to access federated learning services.

This is shown in deployment option D.

6.1.10 oneM2M CSE as MEC Service

Define a oneM2M CSE that is deployed as a MEC service. This CSE will be tightly integrated with the MEC platform, allowing it to leverage MEC services and capabilities to enhance its performance and efficiency.

This is shown in deployment option D.