What Is Edge Computing?

Edge computing allows for data storage and analysis beyond what is possible with only a central data processing location. This brings faster and more reliable insights at the location of data generation, which helps to improve performance and encourage new innovations. Let’s explore the finer details of edge computing, its benefits on modern computing, common uses across industries, and how you can learn more.

What is edge computing?

Edge computing is a type of computer framework designed to help process data more efficiently. As a society, the volume of data we produce grows exponentially yearly, and the computing power needed to store and process this data grows alongside it. Edge computing places computing centers (computers or enterprise applications) closer to the data source to improve processing speeds and enable more comprehensive analysis. 

Edge computing emerged to address the limitations of central data processing. While businesses used to have centralized data storage and analytics stored in the cloud, modern smart innovations and monitoring have made this model unsustainable for many applications. Edge computing allows only the most necessary and important data to be transferred to central data hubs, while the rest of the data processing happens at the site of collection. 

Example of edge computing

For example, let’s say you have a smart thermostat in your home that is set to keep your house at 72 degrees Fahrenheit. Edge computing allows your thermostat to make adjustments immediately after reading your home temperature without needing to send the data to a central hub first and await instructions. This reduces the computational load on main data centers while also improving the effectiveness of your thermostat technology. 

Components of edge computing

When exploring edge computing, understanding common terminology and components can help you better understand how this system operates. Each device and term plays an important role in this computer framework. 

Read more: Information Technology (IT) Terms: A to Z Glossary

1. Edge devices

Edge devices are the cornerstone of edge computing. People use electronic items daily to collect and process data. These include smartphones, sensors, robots, vehicles, and IoT (Internet of Things) devices. You may use edge devices in your everyday life without realizing it, like Amazon Alexa or Google Assistant. By processing data on-site, these devices reduce the need to send large amounts of data to distant data centers or clouds, leading to faster and more efficient computing.

2. Edge gateways

Gateways in edge computing act as intermediaries between edge devices and the broader network. They manage data traffic, ensuring only necessary data is sent through the network. These gateways enable wireless connection and heighten network security.

3. Edge servers

Servers in edge computing are localized and placed closer to the source of data generation. Unlike traditional centralized servers, these edge servers handle data processing and storage near the data source. 

4. Edge processors

Processors within the edge computing framework execute computing tasks, such as filtering, masking, and routing. They are responsible for the computing speed a network has; the more memory a processor has, the faster the network can perform.

5. Edge switches

Switches in edge computing environments manage data flow within a local network. They connect devices, such as edge devices and servers, to create a network. 

6. Edge routers

Routers in edge computing direct data traffic. They determine the most efficient routes for data transmission between edge devices, servers, and the rest of the network. Routers connect multiple switches to create an expanded network.

Read more: What Is a Router?

7. Network edge

The network edge is the boundary between the core network and the network's edge where edge computing occurs. This zone is where data processing and analysis occur closer to the data source without being sent to a central location. You can characterize the network edge by its proximity to the end-users and data sources, which enables faster response times at a lower cost.

Why is edge computing important?

Edge computing allows organizations to decentralize their data processing operations, improving devices' performance in remote locations, reducing the computational load on central data processors, and allowing for more effective bandwidth utilization. One of the ways edge computing does this is by drastically reducing the distance between the data generation and data processing sites. By bringing computing capabilities closer to data sources, such as IoT devices or local servers, edge computing minimizes the physical and network distance data must travel. This reduced distance allows companies to process more data more quickly, accelerating insights and allowing more effective adaptation.

Edge computing also reduces latency by reducing the distance between devices and networks and allowing localized processing. By processing data near its source, data isn’t required to transfer to the central processing center before the next device can take the next step. This makes edge computing hugely important across industries, especially in situations where milliseconds make a difference, like health care monitoring. Edge computing also benefits employee productivity due to quick data processing, employee safety with IoT sensor monitoring, and data collection in remote locations. 

You can see the importance of edge computing economically, as this type of network can handle the influx of data we generate in a cost-effective way. Edge computing does this by only sending necessary data to the central hub while handling the majority of computations locally. 

Who uses edge computing?

Many professionals and industries benefit from using edge computing, but some fields, in particular, are especially suited to the advantages of this technology.

Health care is a driving force behind edge computing, as the technology allows medical facilities to store patient data locally. This allows for increased patient privacy measures by reducing data transfer and minimizing the risk of data loss. In addition, the reduced latency of edge computing improves patient monitoring, real-time data processing during surgeries, and diagnostic imaging. When patients require critical care, waiting for data to be transmitted to a central location and back can take time that patients don’t have. In these cases, edge computing is invaluable. 

Professionals also use edge computing in areas such as:

• Retail: Stores can use edge networks to record inventory levels and streamline checkout processes for customers automatically. 

• Factories: IoT sensors and AI can detect equipment malfunctions at the site and quickly alert workers and managers. Sensors can also monitor efficiency and record operation data points.

• Farming: Systems can detect water and nutrient levels within the soil and adjust equipment accordingly.

• Energy: Oil, gas, wind, and solar farms use edge computing to quickly identify hazards and monitor equipment maintenance.

• Robotics: Many types of robotics, such as autonomous vehicles, collect real-time data to make quick decisions that require faster processing than transmitting data to a central location would require.

• Education: For teachers and students in remote locations, edge computing can bring the classroom experience to locations where traditional models are unavailable. 

• Security: Edge devices often monitor security at specific locations, compiling and analyzing relevant real-time data to provide workers faster information.

• Manufacturing: Edge computing enhances predictive analytics with manufacturing equipment, enhancing quality control and maintenance schedules. 

Advantages and limitations of edge computing

Edge computing has many advantages that make it a useful tool across industries. Some advantages you may find when utilizing this type of computing framework include: 

• Minimized latency

• Faster data collection and processing

• Functionality in remote locations

• Increased response time

• Improved privacy and security

• More efficient use of bandwidth

• Reduced IT costs

As with any type of network framework, you will find limitations. Deciding whether the advantages outweigh the limitations will depend on your use case. Limitations to be aware of include:

• Security challenges that differ from challenges in central IT domains

• Increased complexity requiring expert knowledge to implement

• Lack of standard network architecture

Learn more on Coursera.

You can find a broad range of networking courses on Coursera, each designed to help you build your skills and become career-ready. For beginners, consider Rice University's Fundamentals of Computing Specialization. This seven-course series covers interactive programming, computing principles, algorithmic thinking, and more. Upon completion, you will gain a shareable certificate to include in your resume, CV, or LinkedIn profile.