Edge Computing 101

When cloud computing was introduced, there was a lot of confusion about what it was. Similarly, there is a lot of confusion about the current IT trend of edge computing. Here are the basics.

Some industry experts are touting edge computing as the “next IT transformation”, while others have ranked it as one of the top 10 strategic technology trends for 2019. But what exactly is edge computing? Just like when cloud computing was introduced, there is a lot of confusion surrounding edge computing.

What Edge Computing Is

Although “edge computing” might sound like an exciting new IT technology, it is basically a network topology. Like any other topology, edge computing describes how the elements in this type of network are arranged and connected to each other. In this case, the main elements of interest are:

• The edge devices. These devices generate data. They are typically Internet of Things (IoT) devices, such as smart sensors or web-connected cameras.
• The components that process the data produced by the edge devices. These components consist of hardware and software.

What sets edge computing apart is where the data-processing components are located. In most other network topologies, these components are in a central location. They receive data from various devices, then process it. In an edge computing topology, some or all of the data-processing components are located near the edge devices. In other words, some or all of the data generated by edge devices is processed locally.

The Advantages

Having the data from edge devices processed locally provides several advantages, including:

• The ability to analyze and act on the edge devices’ data in near real time. If a smart sensor detects a serious problem with a piece of machinery, for example, the machinery can be immediately shut down. No time is wasted sending the data to another location for processing.
• Reduced bandwidth. There is significantly less data flowing between the edge devices and centralized data-processing components, saving bandwidth.
• The ability to analyze and act on edge devices’ data when there is intermittent or slow Internet connectivity. This makes edge computing well suited for remote locations such as rural areas that have limited Internet connectivity.

Perhaps the best advantage is that edge computing is not an “all or nothing” proposition. It can be incorporated into traditional network environments so that some data is processed on the edge while other data is handled centrally.

The Challenges

While there are many benefits to implementing edge computing, it’s not without challenges. For starters, the edge devices and local data-processing components need to be set up and regularly maintained. Having to update the software on numerous data-processing components, for instance, can be time-consuming.

Equally important, the edge devices and local data-processing components need to be secured. Edge devices in particular are more vulnerable. As the BrickerBot malware attack demonstrated, IoT-ready devices often have security vulnerabilities such as default passwords that are easy to crack and firmware updates that are easy to spoof.

Finally, companies still need to put systems in place to send the analyzed data to a central repository, assuming they want or need to keep that data. At the very least, they will need a reporting system.

What to Find Out More?

Edge computing holds great promise if it is handled properly. We can provide more information if you are interested in exploring it further.