5G is a game-changer for Industry 4.0 and the telecommunications industry. Providers are scrambling to lay the foundation, despite its challenges.
The key to 5G lies in complementary technology solutions. Massive data volumes and processing as needed for IoT ecosystems relies on more than just 5G. With current solutions using a cloud-based data storage core, the latency of data transfers and network traffic offsets the potential performance benefits of 5G.
What’s the solution? Edge computing powered by single-board computers (SBCs) harness the full potential of 5G to overcome considerable challenges and support next-level IoT ecosystems.
Challenges of Cloud-Based Storage
At its introduction, cloud computing facilitated scalable mass data processing and storage to allow enterprises to adopt remote and hybrid work with real-time collaboration and productivity. It also facilitated IoT uses, especially as the demand for more and more data increased. Cloud-based data storage cores ensure space, scalability, and security for enterprises to gather, store, and process data.
It’s not without its downsides, however. IoT devices live on the edge of the network, so data needs to be sent across large distances to the centralized core for processing and analytics. Responses then need to be sent back to the device or end user. This lag can limit the real-time insights the data provides and increases the network traffic – a problem that will only increase as more devices are added to the system.
This not only limits the IoT ecosystem overall, but neutralizes some of the benefits of AI-enabled smart devices like medical robotics and autonomous vehicles. Data is also susceptible to a breach in transit.
Single-Board Computers for Edge Computing
Data for IoT devices is found at the network’s edge. Device sensors are used to compile data, then send it to the network core, leading to significant lag.
Edge computing keeps the data close to its source – on the network’s edge – and the end user. This not only allows for faster processing as data is processed closer to the device, but also provides real-time insights for decisions. In addition, edge computing’s proximity keeps the costs to a minimum and reduces the risk of data traveling over long distances.
One of the best tools for data processing at the edge is an SBC. This computing platform provides high-volume storage, multiple operating systems, and high-speed memory at lower costs and with lower space requirements.
SBCs are flexible options for data processing at the edge. Unlike PCs, SBCs can be scaled and configured to meet changing or shifting demands without starting over from the ground up.
These are fully functional computers, only built on a circuit board that takes up less space. Each SBC contains the main components of a computer, such as memory, input/output, and a microprocessor, functioning as a computing solution with lower costs and fewer power requirements.
While SBCs can accomplish a lot individually, they’re not capable of supporting every application. They can be configured in clusters, however, which can be used as a small-scale supercomputer with multiple nodes for high storage and memory capabilities. Clusters can be constructed of entirely DIY SBCs, mass-produced SBCs, or a combination of both.
5G Powered By Edge Computing
5G is the next level of cellular technology, expanding on the capabilities of 4G with up to 100 times the speed. With 5G, IoT devices can connect within an ecosystem or virtual network and share data over long distances.
With a centralized data core, 5G’s benefits are limited. Data still needs to travel to the core and back, reducing the benefits of lower latency and faster speeds that motivate its adoption.
With edge computing, data can be processed on the edge, near the end user, for faster processing and insights. There’s virtually no latency, since the data is processed close to the source instead of at the network’s core.
This is beneficial for IoT devices overall, but even more valuable as data processing demands increase with complex IoT ecosystems. As more and more businesses and consumers get on board with IoT devices, processing will need to occur at the network’s edge to ensure rapid insights and lower network traffic.
AI is another consideration for edge computing with 5G. In IoT, AI is used to gain insights from data and make decisions quickly, which can’t occur if the information needs to travel to the cloud center. AI-enabled devices require rapid processing and analytics to sort through high volumes of data and provide quick responses and insights.
When this occurs close to the network edge, information can be processed quickly. Data can also be filtered, ensuring that only vital information takes the time, bandwidth, and risk of traveling to the central core.
Edge Computing as Fuel for 5G Adoption
5G is the hottest buzzword for IoT and telecommunications. Though it offers numerous benefits to increase the performance and capabilities of 4G by using multiple spectrums, it’s not widely adopted at this point. Furthermore, many 4G devices aren’t configured for 5G, increasing the adoption challenges.
Edge computing plays a role in this, too. With edge computing, 5G adoption ensures that the benefits are realized. Otherwise, 5G’s advantages over 4G (reduced latency and improved performance) don’t matter, since they’re offset by the challenges of sending information to the network core.
Bringing the processing to the edge ensures that the potential of 5G is utilized for data processing and analytics. Massive amounts of data can be processed at the source, providing rapid responses and reducing overall costs in data transmission using cellular technology.
Edge computing with 5G also unleashes the true potential of IoT devices for better monitoring, maintenance, and experiences. The data needed for decision-making is collected, processed, and analyzed near the device using edge data hubs, leaving only crucial enterprise data to be send to the centralized storage center.
At this point, 5G adoption is limited. 5G has sporadic use cases and low geographic coverage and limited devices with 5G capabilities, leading to a lower demand. Even with all the components in place, there’s no broad rollout or 5G industry standard.
This creates a circular cause-effect relationship. 5G doesn’t have the necessary coverage or enabled devices, leading to less adoption and lower demand, so the industry doesn’t put as much effort into 5G development. Because there’s less development, there’s still limited coverage and limited devices, so lower demand.
Edge computing can be the solution, even with 4G. Though the capabilities of 4G pale in comparison to 5G, edge computing can showcase what 5G can do and drive the demand for more 5G development and coverage.
Looking to the Future
SBCs, edge computing, and 5G are complementary technologies that can be used together for incredible performance and capability. The computational power and reduced costs of SBCs make them ideal for IoT ecosystems and edge data centers for data processing. 5G fills in the gaps by providing fast data transmission at the edge and to the network core on multiple spectrums, reducing latency and network traffic.
While each is powerful on its own, the combination of these technologies can overcome the obstacles to adoption in IoT devices and act as a key driver in the future of the telecommunications industry.
Jason is the Head of SEM at SolidRun which is a global leading developer of embedded systems and network solutions, focused on a wide range of energy-efficient, powerful and flexible products which help OEMs around the world simplify application development while overcoming deployment challenges.