What is Edge Computing?
Edge computing is a relatively new term. It refers to a distributed method of data processing where computing nodes are near the original data source. Edge computing changes the way of managing data and information. Bringing data computation closer to the source, reduces latency and it can lead to a more effective real-time data processing.
Why is Edge Computing Important?
With the ever-increasing number of IoT devices, we need to think of a faster way for managing information. There are so many apps and devices dealing with real-time data. IoT devices generate a huge amount of data. They must connect to the internet in order to get the necessary information from the cloud or deliver data back to the cloud. For instance, consider Alexa. It’s a smart speaker that works with the cloud. That’s why, it usually takes time for Alexa to process what we say. But experiencing such a significant lag in a self-driving car is totally unacceptable.
Due to the great advances in IoT and applications dealing with real-time data, edge computing has become critical. In an edge computing infrastructure, data doesn’t need to travel such a long distance. Instead, it’s processed within the device itself. Clearly, in this approach, we won’t experience any latency issues. Because the device processes data immediately.
What are Edge Computing Applications?
Now that you understand the importance of edge computing infrastructure, let’s take a quick look at some of its applications in our daily life.
- Autonomous vehicles: As we said earlier, in some cases, even milliseconds matter. Consider an autonomous vehicle which is constantly collecting information about location, speed, neighboring vehicles, traffic conditions and other similar factors. As a result, they generate a lot of data per day. Since self-driving cars should react immediately to any road accident, the collected information must be processed in real time. In an edge computing infrastructure, the autonomous vehicle is the edge of the network. So, instead of moving data to the cloud, it’s analyzed by the car itself. This makes everything faster.
- Security cameras: Nowadays, we see security cameras everywhere. In a cloud computing infrastructure, the device usually sends a massive amount of data to a cloud server which is thousands of kilometers away. This will result in a high network bandwidth usage. But in edge computing, the camera analyzes the data and gets to decide whether or not to store it on the cloud server. Clearly, this has a great impact on the device performance.
- Manufacturing: Edge computing reshapes the way of managing supply chain activities. We can use it to enhance our product quality and to find potential errors in manufacturing. It helps us monitor how product components are assembled and how long they remain in stock. This way, manufacturers can generate new revenue streams.
Advantages of Edge Computing:
In the near future, there will be smart cameras, printers, thermostats and generally smart home appliances everywhere. Research shows that, by 2025, the installed base of IoT devices is forecast to grow to almost 75.4B worldwide. To support these devices, deploying an edge computing infrastructure is essential. Here, we explain major advantages of edge computing deployment.
Time plays a critical role in every business. You don’t want your customers to get frustrated when using your application. In some cases, even milliseconds can make a difference. As mentioned earlier, an autonomous vehicle should continuously gather data about the environment and act immediately. In fact, most of the collected information will become useless after a few seconds. If the network doesn’t transfer the instructions to the vehicle in time, tragic accidents can happen. So, delays can hurt the system in so many ways. It can even lead to extremely serious consequences. Analyzing the information in the edge of the network or close to the data source reduces latency and increases the network speed.
Edge computing categorizes the collected information and processes everything in the edge of the network. It helps us optimize the way of managing information by reducing the amount of data that must travel to the cloud. Simply put, we still need the cloud but only for storing critical information. So, it reduces the bandwidth usage and server resources, thereby minimizing overall costs.
We all know that edge computing is a distributed method of data processing. So, it’s a more secure approach in comparison to cloud computing. The cloud is vulnerable to serious cyberattacks. Hackers can easily disclose the information on the cloud but in edge computing, we only store the relevant data on the cloud. So, hackers cannot access the entire data. Hence, the user’s information is totally safe.
Since the data is processed locally, edge computing doesn’t rely on a server or an internet connection to analyze data. So, when there’s a network problem or a slow internet connection, we don’t need to worry. The device is completely reliable and provides an uninterruptable service.
To Wrap Up
Edge computing is an emerging trend in computer science and it continues to evolve. With the exponential growth in AI , IoT and 5G connectivity, we’ll soon understand the great importance of edge computing. It’s not about eliminating the need for the cloud. Instead, it optimizes your data management so as to enhance your performance, minimize costs and satisfy your customers.