The rise of big data and the Internet of Things (IoT) has led to an explosion in the amount of information that must be processed and stored by enterprises.
Edge computing is one approach companies can take to meet the demands of big data and IoT, but what does it entail? And how does it differ from other data storage and analysis strategies?
We’ll answer these questions and more in this guide to edge computing.
What Is Edge Computing?
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Edge computing is a distributed information technology (IT) architecture
in which client data is processed at the network’s periphery, as close to the
originating source as possible.
Edge computing, or processing, occurs close to users’ devices—as opposed
to in centralized cloud facilities—and is distinguished by real-time
responsiveness.
If an autonomous vehicle detects a collision with another car on its way
home from work, it can immediately alert emergency services and pull over to
avoid further damage.
Edge computing also enables businesses to gain more insights into
customer behavior and preferences; for example, an e-commerce site might use
edge compute capabilities to track customer purchasing habits and offer
tailored recommendations based on previous purchases.
In short, edge systems are designed to process high volumes of
transactions while maintaining low latency times.
What can be done
with edge computing?
The rise of IoT has created an enormous amount of new data that organizations need to collect, process, and analyze in real-time. But without the proper infrastructure to support it, most businesses won’t be able to reap all that their big data can offer.
Edge computing is one-way companies can keep costs under control while harnessing all their sensors’ valuable insight into their operations—which is why some industry experts predict that its usage will skyrocket in 2022.
How Edge Computing
Works
Edge computing, in a nutshell, is taking something that was done by a
centralized computer and doing it on an individual machine—generally using less
energy.
Think of your household thermostat: It’s programmed to turn on or off
based on room temperature, but that’s not happening inside your wall.
Instead, you tell a program running on your furnace what to do when you
trigger it to heat up or cool down.
You could say that your thermostat is edge-computing because it handles
some decisions independently from a central system.
Most of our devices are already performing local computation without
realizing it; we just don’t think about them as an edge-computing architecture
because they don’t interact with other machines as part of their primary
function.
The Difference
between IoT Devices and PCs
While it may seem that edge computing and IoT devices are the same, some
differences to consider. IoT devices typically don’t have as many processing capabilities as PCs
or mobile devices; thus, they rely on cloud computing to crunch numbers and
perform other heavy-duty computations.
The main benefit is that you can save a significant amount of money by
having central resources handle much of your information work without
purchasing more expensive equipment for each office location.
You also gain efficiency since all of your locations will be connected
to a single platform. If any issues arise with an IoT device, you only need to troubleshoot
from one centralized location rather than multiple ones. It makes it easier to identify problems and fix them quickly.
Today’s Best
Applications Of Edge Computing
As more and more applications are designed to consume real-time
information, and as wireless infrastructure becomes faster and cheaper, edge
computing will become an increasingly attractive option for businesses.
Much of an application’s processing power can be shifted from massive
mainframes or central databases onto a microchip near its source.
And even better, by moving processing power closer to users, companies
could lower their server maintenance costs and simplify their IT departments.
Additionally, since most devices (like smartphones) are constantly
connected to nearby cell towers, they have access to far more bandwidth than
traditional servers.
For example, instead of uploading images and videos directly to your
cloud storage provider, you could store them on your phone until you get home
and then upload them all at once—meaning that you would only need one
connection with your provider rather than multiple connections (and multiple
bills).
The Limitations Of
Edge Computing
There are many limitations of edge computing. The concept/idea has been
around for a while, but most companies have not been able to invest in it until
now.
There is a lot of complexity when implementing edge computing
technology; getting everything suitable can be challenging.
Edge computing also needs to be highly secure and reliable. If your
company’s information isn’t safe, you could lose millions of dollars in
minutes.
Lastly, when implementing edge computing systems, you need to make sure
that your IT team knows what they’re doing, or else you could waste time and
money on something that doesn’t work correctly.
Do We Need It?
Edge computing is helpful when a lot of data is being collected.
However, some companies don’t need it because they don’t collect much data.
For example, if you have a small business with just two or three
computers, you might not need to use edge computing.
Another reason that certain companies don’t require edge computing is
that their data isn’t secure enough to transmit data through an insecure
network.
If your company/business handles sensitive information such as credit
card numbers, you want to avoid sending that information over an unsecured
network.
