Device Twins in 5G and Edge Computing

Oleg Gurin

Jul 6, 2023 • 10 min read

Introduction

Convergence of 5G and IoT Platforms

As mobile communication and Internet of Things (IoT) technologies continue to evolve, the potential of their combined use becomes increasingly apparent. 5G offers excellent speed, low latency, and high reliability, making it ideal for connecting IoT devices. IoT, on the other hand, encompasses billions of connected devices that can transmit data in real-time, on a schedule, or on-demand, which are essential for improving efficiency, automation, and personalization of services.

In addition to the obvious complementarity between 5G and IoT, there is a common architectural approach in the development of platforms for these technologies - Cloud Native. This creates conditions for deeper integration between them. It seems attractive to make some functions of the IoT platform standard functions of the 5G architecture.

Cloud Native and Its Role in Modern Networks

Cloud Native is an approach to application development and operations that leverages the advantages of cloud computing. This includes the use of containers, microservices, and continuous integration/continuous deployment (CI/CD) for rapid scaling and high resilience of applications. In the context of 5G and IoT, Cloud Native plays a key role in providing the flexibility, scalability, and efficiency required to handle the massive volume of data generated by IoT devices and to support the high-quality communication demands in 5G networks. This has already led to an interesting development: leading cloud providers - AWS, Azure, and Google Cloud offer ready-made infrastructures for launching 5G networks. This is particularly natural for the Open RAN approach to building mobile networks, which is rapidly gaining popularity.

Purpose of the Article

The purpose of this article is to explore the possibility of convergence between 5G and IoT platforms based on Cloud Native. The focus is on integrating Device Twins into the standard 5G architecture and projecting this solution onto Edge Computing. We will examine the advantages and risks of this approach.

5G Technologies

Evolution from 4G to 5G

5G technology represents the fifth generation of mobile networks and is a significant evolution compared to its predecessor, 4G. It is designed for more efficient, faster, and versatile communication compared to 4G, with primary goals of high data transfer speeds, reduced latencies, energy savings, reduced costs, increased system capacity, and enabling massive device connectivity.

Architecture and Key Components of 5G

The 5G architecture includes several key components such as New Radio (NR) access technology, Next Generation Core (NG Core), and Network Slicing technology. These elements are designed to work together to provide versatile and efficient communication across various applications and industries.

Regarding IoT, the following components should be highlighted:

Network Exposure Function (NEF). NEF is a component in the 5G architecture that facilitates interaction between external systems and services with the 5G network. NEF provides standardized APIs for access to network functions and data while ensuring security and control over how external applications interact with the network.
Network Data Analytics Function (NWDAF). NWDAF is a function in the 5G network architecture that analyzes network data and statistics to support network optimization and provide information to other network functions. This may include analyzing traffic, performance, network congestion, and other aspects.
User Plane Function (UPF). UPF relates to the user plane in 5G and is responsible for the processing and routing of user traffic in the network. UPF plays a key role in ensuring high-speed and low-latency data transmission and is a central part of the user plane in the 5G architecture.
Application Function (AF). AF in the 5G architecture enables the interaction of network capabilities with external applications. AF can use NEF to access network functions and participate in session management, Quality of Service (QoS), and traffic management to support specific application requirements.

Open RAN

Open RAN (Open Radio Access Network) is a radio access network architecture that allows mobile operators to use network equipment and software from various vendors, instead of being reliant on a single supplier for the entire solution. This approach provides flexibility, cost reduction, and stimulates innovation.

Within the context of 5G, Open RAN enables the deployment of networks with high bandwidth, lower latency, and next-generation network capabilities through a modular and open architecture.

Key vendors:

Altiostar: A company that provides software solutions for RAN virtualization and promotes the development of Open RAN through contributions to the O-RAN Alliance.

Mavenir: As one of the leaders in the Open RAN solutions area, Mavenir is actively involved in developing software solutions for the virtualization and automation of 4G and 5G networks.

Parallel Wireless: This company is engaged in developing solutions for unifying 2G, 3G, 4G, and 5G mobile networks through an open RAN architecture.

Nokia: Although Nokia is known as a traditional telecommunications equipment manufacturer, the company is actively involved in Open RAN, providing solutions and technologies for 5G networks.

Samsung: The company implements Open RAN solutions, combining its innovations in 5G with an open architecture to provide operators with flexible and scalable network solutions.

Rakuten: The company is one of the key players in the Open RAN field. Rakuten Mobile, a subsidiary of the Japanese company Rakuten Group, is the world's first operator to have built its mobile network entirely based on Open RAN.

Open RAN continues to gain popularity as a means of enabling more flexible, reliable, and efficient deployment of 5G networks. Key vendors and standards, such as the O-RAN Alliance, play an important role in promoting this architecture.

IoT Technologies

The Internet of Things refers to a network of physical devices equipped with sensors, software, and other technologies that allow them to connect and exchange data through the Internet. This enables the creation of smart environments and systems, ranging from small household appliances to large industrial machines.

Architecture and Key Components

The IoT architecture typically includes four layers: the sensor layer, network layer, management layer, and application layer. The architecture can vary depending on the specific use case and requirements. Key components include sensors, actuators, communication means, data processing, and user interface.

As IoT platforms deal with a large number of devices and need to ensure flexibility and resilience, almost all of them are Cloud Native.

Use Cases and Applications

IoT technology has a wide range of applications in various industries such as agriculture, healthcare, retail, transportation, and many more. It provides solutions such as smart homes, industrial automation, wearable devices, smart agriculture, and health monitoring systems.

Interaction between 5G and IoT

The combination of 5G and IoT technologies can create a synergistic effect. Currently, IoT platforms exist separately from 5G and use it as transport. The migration of some IoT functions into the 5G architecture and subsequent promises looks promising: this convergence has the potential to radically transform industries by providing more efficient and complex IoT applications and services.

More About Cloud Native

Cloud Native is an approach to application development and deployment that utilizes cloud technologies to ensure scalability, flexibility, and rapid time-to-market. Applications built using the Cloud Native approach are typically structured as a set of small, independent, and distributed services, known as microservices.

Microservices

Microservices are a key component of Cloud Native architecture. They involve breaking down an application into multiple small and independent services, each of which performs a specific function. These services can be deployed, scaled, and managed independently of each other, which increases the flexibility and reliability of the system as a whole.

Containerization and Orchestration

The Cloud Native approach is also closely associated with the use of containers for packaging and isolating applications and their dependencies. Docker is one of the most popular tools for containerization. For managing containers on large-scale deployments, orchestration systems like Kubernetes are used.

Advantages

Cloud Native architecture offers a range of benefits such as improved scalability, increased resilience to failures, reduced time-to-market, and optimized resource utilization. This makes Cloud Native an attractive choice for modern applications, including in IoT and 5G networks.

Device Twins in IoT

Device Twins are digital duplicates of physical IoT devices that provide a virtual representation of the state and metadata associated with physical devices. Device Twins are used to synchronize the state between physical IoT devices and a cloud platform. This allows developers to track changes in device state in real-time, as well as implement complex scenarios such as managing groups of devices, creating automation scripts, and handling events based on state changes.

Components of Device Twins

Device Twins consist of three main components: device state information, metadata, and device properties. Device state information provides information on the current state of the device, metadata can include information such as firmware version or location, and device properties allow for the control of the device’s configuration and settings.

Providers and Platforms

Several major IoT platforms, such as Microsoft Azure IoT Hub, AWS IoT, and Google Cloud IoT, offer Device Twins capabilities as part of their solutions for managing IoT devices.

Learn more about Device Twins here.

Integration of Device Twins into 5G

Choice of 5G Component for Integrating

As mentioned above, four standard components of the 5G architecture can be candidates for implementing Device Twins in them: NEF, NWDAF, UPF, AF. The choice of the most suitable one should be based on several criteria. Firstly, it is distribution - the ability to work on resources in a data center as well as at the network edge. Secondly, it is the ability to terminate NIDD traffic, native to LPWAN networks. And, thirdly, the presence of security features both for isolating Device Twins form each other and from external attacks.

Below is a comparison table:

Component	Distribution	Termination of NIDD
NEF	Can be deployed both in a central data center and at the edge to ensure proximity to devices and applications	Possible and may be more efficient when NEF is deployed at the edge to minimize latency and enable local data processing
NWDAF	Usually deployed in central data centers but can be deployed at the edge for more efficient data collection and analysis close to the sources	Possible, but may be less efficient due to the nature of NWDAF as an analytics function rather than an interaction point with devices
UPF	Can be deployed both in the central data center and at the edge for processing user traffic closer to the user	Possible, but may be complicated due to the high-performance requirements and low latency of user traffic
AF	Can be deployed in central data centers or at the network edge depending on the application requirements	Highly suitable scenario, as AF has direct interaction with applications and can benefit from local data processing through Device Twins

From the comparison, it is clear that the most suitable candidates are NEF and AF. NEF is more suitable for lightweight and typical Device Twins, while AF is suitable for heavier ones with special demands on computational and network resources. If you remember that LPWAN devices are typically lightweight and that NEF can offer advanced security options, the winner becomes clear.

Integration of NEF and Device Twins

Conceptual Model

The integration of Network Exposure Function (NEF) in 5G networks with Device Twins in IoT platforms opens new opportunities for optimizing and managing communication between IoT devices and 5G network services. In this context, NEF will serve as an execution environment for Device Twins, which are implemented as microservices, with a significant part of NEF functions possibly being executed by the Device Twins.

Microservices

Architecture and NEF In modern trends of 5G network development, NEF can (and should) be implemented using microservices architecture. This allows NEF to be flexible and scalable. Device Twins, in turn, can be embedded in NEF as microservices, allowing them to perform specific NEF functions such as data processing and network resource management.

Distributed Architecture and Mobile Agents

NEF has a distributed architecture, which enhances its ability to scale and handle a large number of devices. Device Twins can act as mobile agents within NEF, moving through the network following their devices. This can be especially beneficial for resource optimization and performance enhancement in mobile scenarios such as autonomous vehicles or mobile robots.

Benefits and Challenges

Using Device Twins as NEF agents can bring several benefits including increased flexibility, resource optimization, and improved quality of service. It also allows for more efficient use of NIDD: this protocol has a customizable packet size. Knowing what the payload will be, NIDD can be set up very precisely and overhead avoided due to a mismatch between them.

However, this approach also presents certain challenges, including security, data management, and coordination between various agents and devices. Regarding security, additional container isolation measures will be needed, for example, such as AMD SEV.

Use Cases and Prospects

While the integration of NEF and Device Twins is a new direction, it offers interesting prospects for future collaboration between IoT and 5G technologies. For example, in smart city scenarios, connected cars, or industrial IoT, where devices often can be mobile, the use of mobile agents can improve the quality of services and optimize resource usage.

Application in Edge Computing

Edge Computing is a concept where computing resources and data processing are placed closer to the location where they are needed, which reduces latency and improves performance. This is especially relevant for IoT, where devices may generate large amounts of data that need to be processed in real-time.

Device Twins as NEF Agents

By distributing NEF up to edge devices, Device Twins, acting as its agents, can be executed there. In the context of Edge Computing, this allows for more efficient use of network resources, reduced latency, and higher throughput. Importantly, it creates a universal approach to working with IoT devices and adds flexibility to the mobile network infrastructure.

Use Case Scenarios and Examples

Using Device Twins as NEF agents in an Edge Computing environment can be particularly useful in scenarios where high performance and low latency are important. Examples of such scenarios include autonomous vehicles, industrial IoT, smart cities, and real-time telemedicine.

Challenges and Opportunities

Although using Device Twins as NEF agents in Edge Computing offers many opportunities, there are also several challenges, such as ensuring security, data management, consistency, and service continuity in mobile scenarios.

The first issue to address is ensuring code portability from the cloud to the edge device - as servers and base stations and routers are typically implemented on hardware of different architectures.

The second issue is how to ensure continuous and equally strong security context for Device Twins during their migration between nodes and when operating on untrusted equipment (e.g., on a user's network router).

Development Prospects

Considering the growth of IoT and the ongoing deployment of 5G networks, the prospects for integrating Device Twins and NEF in an Edge Computing environment look promising. This can become a key factor in the development of intelligent networks, autonomous systems, and other advanced technologies requiring high bandwidth and low latency.

Conclusion

Key Takeaways

In this article, the intersection and interpenetration of 5G and IoT technologies in the context of Cloud Native architecture were discussed. The main focus is the integration of Network Exposure Function with Device Twins, which allows for the creation of a more flexible and scalable environment. Device Twins, acting as agents of NEF, can provide a high degree of mobility and adaptability, which is extremely important in dynamic network scenarios, especially considering the development of Edge Computing. Importantly, this can be done now without altering the standard 5G architecture, allowing operators to launch value-added services based on this, and consumers to lower the barrier for launching IoT projects.

What's Next

The concept presented in the article opens up a promising direction; however, additional research and innovation are needed to realize the full potential of this integration. Security issues, data consistency, integration with existing solutions, and resource optimization require in-depth analysis and development. Industry professionals, researchers, and developers are encouraged to actively participate in this process, contributing to the evolution of network technologies and creating new opportunities for IoT and 5G in the age of Cloud Native and Edge Computing. An optimal solution in future-generation mobile networks would be to implement a component optimized for Device Twins, meeting portability and security requirements.