Today we are going to explain what edge computing is and will tell you what kind of advantages does it bring to the table. Technologies such as mobile computing and the Internet of Things (IoT) are now indispensable for many industries. The most important of these technologies is information transmission and processing, i.e. information technology (IT). Edge computing is considered as an open IT architecture. It is decentralized and is used to develop technologies where determining the real-time nature of information is important. It also seeks to optimize responses to users by reducing costs.
The IoT (Internet of Things) era has arrived, all things are connected to the Internet. And, with the circulation of large amounts of data, not only can data be aggregated and processed by conventional cloud computing, but also in areas close to users. The focus is on “edge computing,” which processes data at the edge of the Internet of Things. So what are the benefits of edge computing for us?
What is edge computing?
Edge computing is defined as a distributed computing model. A model that allows bringing business applications closer to the place where data is generated and where actions must be performed. This can be supported by IoT devices (Internet of Things) or local perimeter servers. Always with the aim of improving response times to users, while saving bandwidth.
Perimeter computing is essential to overcome the performance and compliance shortcomings of cloud applications and services. For, despite its efficiency, cloud computing does not always meet the response times of mission-critical applications. Additionally, we found that enterprises that need to meet certain levels of data storage requirements may also need more local storage capacity than cloud computing.
Perimeter computing means that data is processed on-site, where it is generated, rather than being sent to a server for processing. It uses miniature data centers close to users distributed at the “edge” of the network. Instead of large data centers, which are generally overloaded. In this way, data is processed closer to where it is generated. This reduces costs and increases efficiency as users connect to nearby servers.
Characteristics of edge computing
One of the characteristics of edge computing is its ability to bring the processed information closer to the source of the data itself. So that the processing of the data itself is done quickly and securely; as close as possible to where the issuing user or the source of this data is located. By enhancing and optimizing the use of electronic devices capable of connecting to the Internet. This way the speed of response will be greater.
Edge computing is generally considered remote assistance. That is to say, it does not require specialized resident technical personnel. If an eventuality or error occurs in the system, its own infrastructure is designed so that it can be easily and quickly repaired by local personnel with little or no technical expertise. It is also staffed, if necessary, by a very small number of specialized personnel who centrally manage the site from a remote location.
Latency and reduced costs are key features of edge computing. The edge is the location closest to the subscriber and where data is processed or stored without being transferred to a central location. This provides greater control of the information because processing is done very close to the source of the data. It relies on a specific service or application to optimize cost, performance, and user experience.
Edge computing is mainly used in companies that require a faster response. That is, the latency, which defines the time required to collect and process data on a network, has to be reduced. This is achieved by processing the data at the site where it is collected, instead of having to wait for it to be processed on a central platform, as happens in the cloud. This provides greater benefits to companies.
How edge computing is different from cloud computing?
There is more than one difference between edge computing and cloud computing. For starters, let’s remember that in cloud computing, data is centralized. Whereas edge computing uses miniature data sets distributed at the “edge” of the network. Edge computing is responsible for classifying all this data, in order to determine which of them should be sent to processing centers and which can be processed locally.
Another difference, no less important to highlight, is cost and speed. The cloud has a higher processing capacity and its cost is lower, but the response is not always fast enough as expected. In contrast, perimeter computing has a higher cost, but its response speed is considerably faster. In other words:
- Edge computing = higher cost, faster response speed.
- Cloud computing = lower cost, slower response speed.
Is edge computing similar to fog computing?
Although in principle these two concepts maintain similarities in that they both use greater and more intelligent data processing capabilities in a faster way where they originate; they have clear differences between them in terms of where these greater processing capabilities are located. That is, perimeter computing focuses on data storage and processing processes, directly on the end devices or on the links to other devices that connect them.
Fog computing, on the other hand, brings those increased capabilities to the network level of a local area, which connects end devices to the cloud. In other words, edge computing refers more to the processing on the end devices while fog computing refers to the network that connects these devices to the cloud. Hence, these two concepts rather than being similar could be considered as necessary complements to ensure secure information.
What are the benefits of edge computing?
Let’s take a look at some of the advantages that the use of edge computing brings to companies:
- The speed and costs of the data transmission service are greatly favored due to the fact that the data processing is done in the same place where it is generated. This, as we have said before, leads to a much faster response to the user. In addition, although the cost of edge computing is higher at the time of purchase, in the long run, it will result in savings due to the data processing model.
- Thanks to intelligent distributed data storage systems, large IoT data sets can be analyzed without the need to send them to the server room. This speeds up the decision-making process and allows you to reduce costs. Most likely, even the proliferation of the 5G network will not mean that data collected by autonomous cars, drones, or aircraft will be sent to the server room. Quite the contrary, it allows data processing to be streamlined.
- Better privacy and data management, as currently, data collected by IoT installations is quite vulnerable to theft or falsification. But eventually, awareness of their existence will increase and such threats will affect the stage of data transmission to server rooms over public networks. In this scenario, edge computing will provide greater data security and prevent a single outage from bringing down the entire network.