Categories: Tech Explained

What is mist computing and how does it work?

According to a study by IDC, it’s predicted that there will be 55.7 billion IoT (internet of things) devices by 2025. Although cloud computing has been a large part of the internet of things, businesses are increasingly exploring fog and edge computing and, more recently, mist computing. But what exactly is mist computing and how can its data processing capabilities be leveraged?

What is mist computing and how does it work?

Mist computing puts all of the processing power at the extreme edge of the network on the sensors embedded in a physical device (such as a mobile phone or security camera), making it an extension of edge computing. Through microcontrollers and microchips embedded in these devices, mist solutions enable local decision-making and real-time data processing. 

Data processed on the devices can be sent to edge servers and gateways that store the necessary data at the edge. Then, depending on the application, the data can then be forwarded to the cloud. 

However, because all of the computing power is placed on the sensors themselves rather than an edge device, the processing capabilities are limited. As a result, mist computing is best used for managing smaller amounts of data.

Smart devices

Devices such as smartphones and smart home devices have become an increasingly large part of mist computing. As an example, if a sensor embedded in a furnace detects any abnormalities, it can send a notification to your smartphone alerting you that something is wrong.

Although mist computing is often used for smaller, consumer-based applications due to its limited data processing capabilities, businesses can still leverage its local data analytics. Public transportation, for example, is an area where this is becoming increasingly prevalent. 

With local data processing, information on a bus’s location can be gathered through IoT sensors on the bus and relayed to commuters through their smartphones.

The benefits and challenges of mist computing

As mentioned earlier, mist computing only allows for the processing of lightweight data. This can be a disadvantage for environments that handle larger amounts of data. However, this can actually work as an advantage in some cases. Since only essential data is sent to the end devices (such as smartphones, computers, and servers), you are able to conserve both bandwidth and battery power.

One additional advantage to this is enhanced data security. Because data is processed locally, sensitive data can be encrypted or removed before it is shared over a network connection or forwarded to the cloud. Local data processing is also possible through fog computing, making fog computing another viable option for instances where security is a concern.

Mist computing vs fog computing: how different are they?

Mist and fog computing share a lot of similarities. Both work with edge computing, offer local data processing, and help to reduce latency. But while mist computing lives on the extreme edge of the network, fog computing acts as a waystation between edge and cloud computing.

What sets them both apart is where and how the computation happens. Mist computing processes data on the sensors themselves, while fog computing processing happens on the fog nodes. The bottom line is that the amount of data that you can process with mist computing is considerably less than what can be processed through fog or edge computing.

In conclusion

For applications that handle smaller amounts of data, implementing a mist solution can be a great way to leverage its real-time data processing and local decision-making capabilities. However, every application is unique, and you’ll need to consider all of your options and the potential downsides before committing to a solution. 

If you have any questions, reach out to one of our solutions specialists today.

Claireice Mathai

Claireice Mathai is a content creator for OnLogic. When not writing, she enjoys playing guitar and gaming.

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Claireice Mathai

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