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What You Need to Consider Before Implementing IoT Edge Computing

What You Need to Consider Before Implementing IoT Edge Computing

IoT edge computing is widely seen as one of the most exciting developments in technology in a very long time. It has the potential to revolutionize both business and everyday life. At the same time, IoT edge computing does have its drawbacks. With that in mind, here is a quick guide to what you need to consider before implementing IoT edge computing.

The basics of IoT edge computing

IoT edge computing is a form of distributed computing. Its defining feature is that it returns process power to end devices and local servers. This is the exact opposite of the approach taken in cloud computing.

Cloud computing is also a form of distributed computing. The key difference is that in cloud computing, the end devices are little (or nothing) more than interfaces. They simply collect data and send it to the cloud. The cloud does the processing work.

Many implementations of IoT edge computing are effectively hybrid implementations of IoT edge computing and the cloud. This approach can be the ideal way to leverage the benefits of both options.

IoT edge computing compared to cloud computing

If you are considering implementing IoT edge computing, your main alternative is likely to be cloud computing. With that in mind, here is a quick guide to how the two options compare.

Speed vs power

The fact that IoT edge computing solutions can process data on-site means that they can operate much quicker than the cloud. That speed advantage, however, will always have a cap on it. As processing requirements go up, the speed benefit from using IoT edge computing will reduce. At some point, the cloud will become the faster option.

The cost of implementation

It is very difficult to make a fair, like-for-like comparison of the implementation costs of IoT edge computing versus cloud computing.

Strictly speaking, IoT edge computing has lower implementation costs. This is because it can be implemented without a data center. In the real world, however, most businesses interested in IoT edge computing would either already have access to a data center. Even if they didn’t own one themselves, they could use an as-a-service offering.

Taking the costs of building a data center out of the equation, the implementation costs of IoT edge computing are likely to be higher than the implementation costs of the cloud. This is because edge devices need to have much more powerful hardware than cloud devices.

Running costs

Both IoT edge computing and cloud computing require staff resources. They are therefore fairly equal in that regard.

With IoT edge computing, the main running cost is likely to be the cost of electricity. The fact that IoT edge devices are doing so much more work than cloud clients means that they need more fuel. In some cases, it may be possible to offset these costs by using on-site sources of renewable energy. For example, some buildings may have solar panels.

With cloud computing, the local devices need relatively little energy. The data center will need energy. Again, however, there may be the option to use on-site sources of renewable energy. Taking the data center out of the equation, the main costs of cloud computing are internet traffic and cloud processing costs.


At present, IoT edge computing is much more complicated to manage than the cloud. The differential will probably be reduced over time. It may even be erased. Realistically, however, this is likely to be a lengthy process.

The main issue to resolve is the complete lack of standardization in edge devices. This is fairly common whenever a new form of technology is introduced. It’s equally common for a solution to be found somehow.

For example, technically, the DVD format wars are very much still ongoing. Practically, however, they have ceased to matter. This is because DVD players now read multiple formats of DVD. Likewise, blu ray players are backward-compatible with DVDs.

Right now, however, the cloud is a lot more mature. It, therefore, has the benefit of a wide range of solutions to make it easier to manage.


Processing data locally eliminates (or at least reduces) the need for it to be moved. This reduces the opportunities for anything to go wrong as a result of the move. This could mean the data being intercepted in transit. It could also mean a disruption at the data center.

On the other hand, protecting a dispersed range of devices creates much more logistical complexity than protecting a data center. As the old saying goes, “Complexity is the enemy of execution.”.

It is true that using a data center creates a single point of failure. The other side of this point, however, is that it means you can focus all your resources on one specific place. If you do this properly, your data center will essentially become a data fortress. It will be perfectly equipped to repel all kinds of attacks.

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