Edge Computing + IoT + Private Networks – How New Technologies Implement Digital Transformation

The new services enabled by the Edge Computing network architecture, associated with IoT devices, can be enhanced by the broad connectivity offered by Private 4G/5G Networks, enabling the introduction of the set of technologies known as Industry 4.0.

Bringing this into a practical context, a company’s Digital Transformation can be implemented by joining the forces of these new solutions. Simultaneously, data obtained from the shop floor can be processed and formatted using Big Data techniques, analyzed and understood with Data Analytics, and solutions can be found through AI and ML.

This article will briefly describe these technologies, explore the gains provided, and discuss their implementation.

Understanding the Concepts

First and foremost, let’s define these fundamental concepts, which have been taking shape over the last few years and have now reached a high degree of maturity, being utilized across industry, commerce, and services with significant gains in productivity and reduction of operational costs:

1. Cloud Computing

Network architecture has undergone a profound evolution over the last 50 years. At the beginning of the so-called 4th Industrial Revolution, the computing environment in companies and universities consisted of mainframes with simple access terminals. After this period, there was a shift toward PCs, with all software running locally on the machines. The evolution continued with the introduction of the client/server model, followed by the architecture of public and private clouds. Now, with the need for agility, minimum response times, and — in many cases — critical use cases, the Edge architecture is rapidly asserting itself:

Cloud computing means on-demand access to a network, which provides a shared set of configurable computing resources (networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort from the service provider.

Cloud architectures are classified into different types, depending on the level of control that the company or organization has over the cloud computing infrastructure and the cloud computing resources they use. The four main cloud architectures are: private cloud, public cloud, hybrid cloud, and multicloud. But after all, which one is ideal for your business?

Below, we will explain each of these types of architecture in detail and their advantages:

• Private cloud: A private cloud is a cloud infrastructure exclusive to one organization. The company has total control over the architecture, security, and compliance of the cloud resources. The private cloud can be managed by the organization internally or outsourced to a company that offers private cloud services. This architecture is ideal for companies that want a high level of control over their data and cloud computing resources.
• Public cloud: A public cloud is a model in which cloud computing resources are offered by third-party cloud service providers. This architecture is highly scalable and flexible, allowing companies to pay only for the resources they use. The public cloud is ideal for companies that do not have many resources to invest in IT infrastructure and want to take advantage of the scalability and flexibility offered by the public cloud.
• Hybrid cloud: A hybrid cloud is a combination of public and private clouds, allowing companies to enjoy the benefits of both architectures. The hybrid cloud can be configured in several ways, depending on the organization’s needs. For example, the organization can keep its most sensitive data in the private cloud and use the public cloud for less critical resources. Or, the organization can use the public cloud to meet peak demand needs and the private cloud for daily needs.
• Multicloud: A multicloud cloud is an architecture that allows an organization to use multiple cloud providers, public or private, at the same time. This architecture offers more flexibility and resilience than a single public or private cloud. However, managing multiple cloud providers can be complex and may require a greater investment in management and systems integration.

In summary, the choice of cloud architecture will depend on the organization’s needs and available resources. The private cloud is the most secure but can also be the most expensive. The public cloud is highly scalable and flexible but may be less secure. Hybrid and multicloud clouds offer a balance between security and flexibility but can be more complex to manage. Currently, about 90% of workloads are processed through cloud data centers.

The stored data can be images, videos, files, and programs, with on-demand access in 3 service categories:

• SaaS: The use of software applications hosted in a public cloud, with payment based on usage volume (Pay As You Go).
• IaaS: IT infrastructure hosted in a service provider’s cloud. Servers, storage, networks, and operating systems.
• PaaS: Development and publication of software applications in a hosted environment, with agility and without the need to configure infrastructure.

2. Edge Computing

Edge Computing (MEC), on the other hand, brings processing and storage resources closer to where they are needed, relieving the cloud (the core of IT & Telecom networks).

Edge/Fog Architecture provides:

• Greater protection for sensitive data that should not be propagated across the network;
• Minimal delays, suitable for certain mission-critical applications (URLLC);
• Lower demand on network bandwidth;
• Operations even when networks are interrupted;
• Reduced energy consumption due to dedicated chipsets and devices.

In telecommunications, Edge Computing enables enhanced content delivery and the deployment of virtual network functions for 5G rollouts.

In manufacturing, it allows for the establishment of intelligent and efficient production lines and warehouses through advanced robotics and sensors (real-time analysis and action based on IoT/sensor data).

In transportation and logistics, it enables Automated Guided Vehicles (AGV) and autonomous cars, as well as advancements in cargo monitoring and intelligent transportation systems.

In retail, it enables a reinvented customer experience through smart mirrors, smart shopping carts, automated checkout, digital signage, targeted advertising, and real-time inventory tracking and replenishment.

Some definitions regarding data processing:

• There are different types of data access/sources: laptops, smartphones, IIoT, tablets, sensors, smart appliances, drones, robots, connected cars, edge gateways, etc;
• Smarter edge devices generate massive volumes of data, both real-time and non-real-time;
• Many data points have an expiration date: why send them to the Cloud?;
• Statistics, comparisons, and data combination should be performed in the core (Cloud servers) for the generation of reports and insights.

Some use cases served by the Edge-Cloud architecture:

• Smart Cities;
• Smart Grid;
• Autonomous vehicles / drones;
• Virtual & Augmented reality (VR/AR);
• Industrial IoT;
• Real-time multiplayer gaming.

3. IoT

IoT consists of smart, connected sensors and actuators used for data collection and process improvement, allowing companies to detect inefficiencies and problems, saving time and money while supporting business intelligence efforts.

Specifically in manufacturing, IIoT (Industrial IoT) has great potential for quality and process control, sustainable practices, and supply chain traceability. In an industrial environment, IIoT is fundamental for processes such as predictive maintenance, field services, energy management, and asset tracking.

These devices have been operating since the era of 2G networks with GPRS connectivity. There are also those that operate on unlicensed networks such as SigFox, LoRa, RPMA, Symphony Link, and Weightless.

IoT in 4G LTE:

NB-IoT and Cat-M1 are specifications for IoT devices standardized by 3GPP in Release 13. Although complementary to each other, they are intended for different types of use cases based on the required network resources:

• NB-IoT supports low-complexity devices with very narrow bandwidth (200 kHz) and a data peak of around 250 Kb/s. An NB-IoT carrier can be deployed in the guard band of an LTE carrier without impacting licensed band traffic.
• On the other hand, Cat-M1 operates with a 1.4 MHz bandwidth with higher device complexity/cost than NB-IoT. This allows Cat-M1 to reach data rates of up to 1 Mbps, lower latency, and more precise positioning capabilities. Cat-M1 supports voice calls and mobility.

NB-IoT and Cat-M1 devices can remain dormant for long periods, which significantly reduces the device’s power consumption. The most common NB-IoT use cases include meters and sensors for utilities. Typical Cat-M1 use scenarios include connected vehicles, wearables, trackers, and alarm panels.

However, there are restrictions for these IoT devices in 4G: low massive deployment (terminals per km²) and low data rates. 5G networks were developed to resolve these and other issues.

IoT in 5G NR:

The first version of the 5G NR standard, 3GPP Release 15, supported two classes of IoT devices: Cat-M1 for 1.4 MHz channels and NB-IoT for 200 kHz channels.

With the improvements introduced in 3GPP Release 16, both device classes can coexist with 5G devices on the same NR channel. Release 16 also introduced specifications for 5G devices for URLLC to meet the stringent requirements of mission-critical IoT, supporting millisecond latencies and 99.9999% reliability.

In Release 17, 3GPP specified a lightweight version of the 5G standard called 5G Reduced Capability (RedCap) to meet low-cost and complexity needs. 5G RedCap will provide hardware vendors with a viable option to develop 5G IoT devices that can compete with their 4G counterparts in price. RedCap devices can support 150 Mbps / 50 Mbps in downlink / uplink.

RedCap can coexist with these IoT device layers and eMBB devices on the same 5G NR channel, which was initially referred to by different names: NR-lite, NR-light, or Industrial Wireless Sensor Networks (IWSN).

The initial standard use cases for 5G RedCap in Release 17 are listed below:

• Industrial sensors: pressure sensors, humidity sensors, thermometers, motion sensors, accelerometers, and actuators;
• Surveillance cameras: smart cities, factories, and other industrial sites;
• Wearables: smartwatches, health-related devices, and medical monitoring devices.

4. Private Networks

Industries and companies are undergoing an unprecedented digital transformation, driven by the adoption of cloud-native applications and services, Internet of Things (IoT), data analytics, artificial intelligence, augmented reality, and blockchain. Although the degree of implementation of these technologies varies in each segment or vertical, a common factor remains true across the board – the need for connectivity and mobility in a fast and stable network.

A Private 5G Network is a corporate network that provides communication connections for users belonging to a private organization, while offering specific application services tailored to the needs of each business. For industrial applications, the ability to deploy mobile networks to meet the reliability, latency, and security requirements of critical applications is fundamental to the new wave of cyber-physical systems known as Industry 4.0.

Private 5G Networks can be implemented in various modes, which are much more flexible than previous generations of mobile communication. The allocation of 5G frequencies to establish private networks has been introduced and standardized in several countries in recent years. In Brazil, 100 MHz of bandwidth was allocated in the 3700-3800 MHz range. The new 5G frequencies for private network use are expressed in various terms, such as unlicensed, private, local, or shared frequencies, with the service known as CBRS (Citizens Broadband Radio Service) being a primary example in use in the USA.

The virtualization and “cloudification” of network functions in 5G allow 5G networks to run via software in a hardware-agnostic environment. Mobile networks implemented with software – which are not tied to dedicated hardware equipment – enable private network customers to reduce costs and increase efficiency in deployment and operations.

Private 5G Network Architectures

The Enterprise sector is moving rapidly toward Digital Transformation, despite successive economic crises, the pandemic, and geopolitical problems that have plagued the world. Large-scale companies with a significant presence in their field are undergoing unprecedented changes, driven by the adoption of cloud services, IIoT, Data Analytics, AI, AR/VR, Edge, and Blockchain. Although the degree of implementation of these technologies varies in each vertical, there is a common factor: the need for connectivity in a fast, secure, and manageable network.

A Private 5G Network is a corporate network that provides communication connections for users belonging to a private organization, with specific application services tailored to the needs of each business. For industrial applications, the ability to deploy mobile networks to meet the reliability, latency, and security requirements of critical applications is fundamental to the new wave of cyber-physical systems known as Industry 4.0.

These networks can be implemented in various modes, much more flexible than those of previous 3G and 4G generations. One can use equipment completely separate from public networks, or Private Networks can be implemented with varying degrees of sharing with operators.

For RAN sharing, the two most commonly used solutions are known as MOCN (Multi-Operator Core Network) and MORAN (Multi-Operator RAN):

• In the MORAN architecture, everything in the RAN (antenna, tower, site, power), except for the radio spectrum, is shared between the private network and the operator. The network Cores are kept separate.
• In the MOCN architecture, the networks share the same RAN, which means the bands are also shared. The network Cores are kept separate. MOCN is the more resource-efficient solution, as it offers mobile operators the opportunity to pool their respective spectrum allocations, resulting in greater trunking efficiency.

In addition to the solutions above, Private Networks can be implemented by sharing part of the public operators’ Core in various formats, as shown in the figure below:

Currently, equipment for independent Private 4G/5G Networks is supplied in a small rack, with a server running the Core — fully implemented in software (VNF/CNF) — and with macro and/or small cells on-site (on-premises). If necessary, local processing capacity can be implemented via Edge Computing.

Edge + IoT + Private Networks

As seen above, Private Networks, Edge Computing, and IoT are complementary technologies that enable the introduction of the so-called Industry 4.0. IoT devices generate vital data traffic, which is transported by 5G networks, while edge computing stores and processes this data with low delay and high reliability and security, providing important insights for companies via AI and ML.

A more pertinent issue is that 5G networks will take a long time to reach users. The schedule established by Anatel predicts nearly 10 years for 5G to reach small towns. 4G coverage, 10 years after its auction, still has low national coverage, especially in rural areas. Agribusiness, manufacturing industries, warehouses, retail, ports/airports, mining, hospitals, and utilities will need to build their own 5G networks if they want broad and reliable coverage.

The implementation of Private 5G Networks is becoming increasingly cost-effective, with various solutions from both traditional vendors and new players developing OpenRAN solutions. Basically, what is required are:

• The network core, typically implemented via software on a high-capacity server;
• Base stations (gNodeB);
• Antennas;
• The backhaul (usually fiber) for external connectivity.

The combination of these three technologies enables the rapid introduction of advanced use cases, with data processing using data analytics and ML/AI techniques at the network edge, providing feedback and insights for better operation and profitability.

• Big Data is the term used to describe a large volume of data – both structured and unstructured – that floods a business on a daily basis. But it is not the amount of data that is important; it is what companies do with this data that can bring value. Data analysis is the key to unlocking the value of Big Data.
• Data Analytics is the process of examining data using statistical and programming techniques to discover patterns, trends, and valuable insights. Companies use data analytics to make assertive and more informed decisions, to improve efficiency, and to better understand their customers.
• AI (Artificial Intelligence) is a technology that allows machines to perform tasks that would normally require human intelligence, such as speech recognition, computer vision, and decision-making. AI is used in many different applications, including chatbots, virtual assistants, and autonomous cars.
• ML (Machine Learning) is a subset of AI that allows machines to learn from data and improve their accuracy over time. ML is used in many applications, including fraud detection, demand forecasting, and sentiment analysis.

What is the path to adopting new network technologies?

Despite these technologies being mature and having many commercial solutions available, most entrepreneurs across various verticals — from hospitals to the field — need “evangelization,” as they do not deeply know these possibilities. This is a process that must be carried out while respecting local and sectoral realities.

Business owners, especially in Brazil, have an arduous and ever-growing daily mission to keep their businesses operating against a series of adversities in a business environment that is not always favorable. The lack of incentives and knowledge are also factors that prevent greater market penetration of new technologies. One must speak the language of these entrepreneurs, showing the countless possibilities for greater efficiency and profitability that are available at this very moment.

Edge UOL has a team of specialists in all these technologies, and we can take your company to a new level of operation. Contact us here and discover the solutions available for your business.