Both IoT and Edge Computing are here to stay, as they play very important roles in business and society. But this is where they differ.
Python are also popular languages for the IoT ecosystem.
It's also important to understand that many IoT devices require a network connection to function properly or communicate with other devices. For example, some refrigerators use network connections to enable shopping lists to be synchronized with mobile devices. Thermostats (like Nest devices) require network connections to be able to communicate with smartphones for remote control.
These connections mean that IoT devices require low latency connectivity, meaning a device can send and receive data without noticeable delay. Low-latency network connections are especially important when IoT devices help power mission-critical infrastructures (such as robots, smart factories, and autonomous vehicles).
One of the biggest problems with embedded systems is security. Due to lack of local storage space, system updates and data processing can be quite challenging, especially when large amounts of data are required. In many cases, these updates simply do not run. This often happens because companies that build/develop IoT devices choose to save money on internal storage space. And given the cost of development, most manufacturers choose not to worry about dealing with updates.
But not all IoT devices are simply small form factor embedded devices that serve a singular, isolated purpose. IoT Edge devices are a completely different beast.
Before we get into that, let's answer another important question.
What is edge computing?
Simply put, Edge computing is computing handled at the source of the data. Let me explain by illustrating the traditional data computing method.
Let's say you have a bus and the bus allows passengers to swipe a card that tells the driver whether the person has enough credits on the card to allow them entry. In a traditional system, the card is swiped and the data is then transmitted (via a wireless connection) to a centralized hub, where the computing is taken care of. The centralized server checks the user's account, finds that the user has sufficient funds in the account, and transmits an affirmative response to the originating system. The passenger can get in and the driver drives.
If this example bus device is completely isolated, without needing to compute data and then (at some point) synchronize the computed data with a centralized server, it is simply an IoT device. If, however, we add synchronization from a centralized server to the localized computer, we have IoT Edge Computing.
In the IoT/Edge Computing environment, this process goes something like this:
The passenger enters and swipes the card. The Edge Computing device is already synchronized with the centralized server and contains an updated database of information, so it immediately checks the user's account and arrives at an affirmative answer, so that the passenger can board the bus.
The Edge Computing example is much faster than the traditional example because it does not need to transmit any data during the transaction. At specific intervals, however, the Edge Device will have to synchronize the stored data with the centralized server, otherwise the information stored on the device will become out of date. This synchronization happens when the device is not in use. The Edge Computing example is also more secure because data synchronization can be better controlled.
Edge Computing has become quite important for companies and services, where it is not always possible to have a constant connection to the Internet, but transactional data must be computed. And so these types of devices are IoT that can process data in real time and synchronize data when necessary.
Therefore, where IoT devices can get by with minimal hardware requirements (internal storage and CPU), IoT Edge Computing devices must include more internal storage and more powerful processors. This is especially true in use cases where databases can get quite large (like our bus example). When you have potentially hundreds of thousands (or even millions) of user accounts to compute, resources must be up to the challenge.
Edge Computing developers also have more to consider than standard IoT device engineers. The operating system not only needs to be able to handle the localized task, but it must also be able to automatically synchronize and process data (when the device finds a network connection or arrives at a specific location. Of course, IoT developers and Edge Computing devices must have security in mind. Without a high level of security, Edge Computing IoT devices can easily put user data at risk.
Conclusion
The division of IoT and Edge Computing can sometimes be very blurred because IoT can be employed as Edge Computing devices. The biggest difference is the ability to not only compute data (in real time) locally, but also to synchronize that data with a centralized server (at a time when it is safe – and possible – to transmit).
Both IoT and Edge Computing are here to stay, as they play very important roles in business and society. If you don't already work with IoT and Edge Computing in your company, it won't be long before you do.
If you liked this, be sure to check out our other IoT articles.
- 6 Ways IoT Technology Can Improve Your Manufacturing Operation
- IoT: 5 predictions
- Internet of Things: The next level of security
- IoT trends
- Is your IoT security robust enough?
Source: BairesDev