The Internet of Things (IoT) edge computing refers to placing data processing and analysis closer to connected devices with sensors and actuators within an IoT infrastructure. What are the benefits of moving IoT to the edge?

Let’s dot the i’s and cross the t’s in how IoT and edge computing relate and why more and more IoT experts rely on edge computing in developing IoT solutions.

Traditional IoT devices – a relic of the past?

IoT devices are hardware components with sensors and actuators capable of connecting to the Internet. Having no embedded operating system, IoT devices can perform one or just a few execution threads at a time.

Due to low computing power, standard IoT devices perform little data processing locally. Instead, using embedded sensors, they gather information about the environment and transmit the data over the network to the cloud for analysis and processing. You can imagine the amount of data flowing back and forth in every IoT ecosystem if, according to Statista, the number of devices worldwide is forecast to almost double from 15.1 billion in 2023 to more than 29 billion in 2030.

Transmitting large data volumes leads to a decrease in sampling resolution and frequency. It also incurs delays in time between the very collection of data and actions performed on the device. For instance, in a simple IoT infrastructure consisting of a device, network, and backend server, the backend server will easily analyze usual images transmitted from the device. At the same time, once the device collects HD video data, the backed server will receive relatively low-resolution video samples at low frame rates.

Nevertheless, the seemingly restrictive limitations of having no embedded operating system and memory components still contribute to the utilization of simple IoT devices. A traditional IoT device can efficiently utilize its processor and perform operations in exact timing, simply because there are no other tasks, except for the running one, competing for the CPU resources. In addition, the absence of operating systems makes simple IoT devices less prone to classic OS-based cyber attacks.

Edge computing joins the battle

In an IoT environment, edge computing implies placing computational resources closer to the data source. The first and foremost use case of edge computing refers to empowering IoT devices with computing resources and transforming them into edge devices capable of processing data locally without the need to send it over to the cloud for further analysis.

Edge devices are capable of multitasking and running several applications at a time. Compared to simple IoT devices that require a physical connection to update their firmware, it is much easier to keep the software and firmware of edge devices up-to-date with available over-the-air (OTA) updates.

Being equipped with sensors and actuators and, at the same time, empowered with computational resources, edge devices become full-fledged elements of the IoT ecosystem. That is how many people use ‘an IoT device’ and ‘ an edge device’ terms interchangeably.

The examples of IoT edge devices range from autonomous vehicles requiring real-time data analysis close to the data source to remote patient monitoring solutions and smart home appliances capable of local computing. Edge devices are rapidly replacing ‘traditional’ IoT devices. Statista reports the expected growth of the edge computing market, reaching $274 billion by 2025.

Nevertheless, utilizing edge computing is not always about placing computer power in the devices themselves. Computational resources can be put closer to the data source by installing a local edge server to capture data before transmitting it to the cloud. Another use case of edge technology refers to placing edge servers at the radio base stations creating multi-access edge computing data centers at the network edges. With the possibility to analyze data locally or at the network edges, less information is sent to the cloud, reducing latency issues to a minimum and releasing more resources for AI/ML-powered data analysis at backend data servers.

Benefits of adopting edge computing in IoT

So, what are the exact benefits of edge computing, and why is the technology gaining traction?

Reduced network latency

Edge computing enables data processing physically closer to the data source, making the trip the data takes from a sensor to the server and back much shorter. Rapid responses are especially valuable to IoT ecosystems where near real-time processing and actions are required.

Optimized network bandwidth

Edge computing optimizes network bandwidth utilization by processing and filtering data closer to the data source. It allows for higher network bandwidth and ensures the necessary information smoothly travels to the central cloud and back.

Improved IoT network security

Edge computing won’t become a magic pill against all possible cyber threats, but it still offers certain security benefits. Leveraging local positioning in an IoT ecosystem, an edge server can become a rescue for companies concerned about storing all their data in remote areas. By locating edge servers on-premises, companies can better control access to information and make sure that some of their data never leaves a certain perimeter.

Wrapping it up

The marriage of IoT with edge computing is not just the next step in the IoT world’s evolution. It is a new milestone in data analysis mechanisms. Due to the IoT edge, the journey from data collection to decision-making becomes an expedition measured in milliseconds.

Edge computing solves the problems of high network latency and low bandwidth, empowering IoT ecosystems with real-time data analytics capabilities and making IoT devices more intelligent, adaptive, and secure.

This article was provided by Daniel Brunson