What is edge computing? Is it the future?

Technologies such as mobile computing and the Internet of Things (IoT) are now indispensable to many industries. The most important of these technologies is information transmission and processing, that is, information technology (IT). The edge computing is considered an IT architecture open . It is decentralized and is used to develop technologies in which determining the nature of information in real time is important. In addition, it seeks to optimize responses to users by reducing costs.

The era of IoT (Internet of Things) has arrived, in which all things are connected to the Internet. And, with large amounts of data circulating, 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?

The Edge computing or say in Spanish: computing edge or perimeter computer, is defined as a model of distributed computing. A model that enables business applications to be brought closer to where data is generated and where actions must be taken. For this, it 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.

Edge computing is essential to overcome performance and compliance gaps in cloud applications and services. Because, despite its efficiency, cloud computing does not always meet the response times of mission-critical applications. Additionally, we find that companies that need to meet certain levels of data storage requirements may also need greater local storage capacity than cloud computing.

Edge computing means that data is processed right there, where it is generated, rather than 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, the data is processed closer to where it is generated. Achieving reducing costs and increasing efficiency while users are connecting to nearby servers.

Edge computing features

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 carried out quickly and safely; as close as possible to where the issuing user or the source of this data is located. Enhancing and optimizing the use of electronic devices capable of connecting to the internet. In this way the response speed will be higher.

Generally, the Edge computing is considered remote assistance . In other words, it does not require resident specialized technical personnel. In the event of an eventuality or a system error, your own infrastructure is designed so that it can be quickly and easily repaired by local personnel with little or no technical expertise. It also has, if necessary, a very small number of specialized personnel who are in charge of managing the site centrally from a distant location.

Latency and reduced costs are key characteristics 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. In this way, greater control of the information is obtained, thanks to the fact that the processing is carried out very close to the source of the data. It relies on a specific service or application to optimize cost, performance, and user experience.

The Edge computing is mainly used in businesses that require a faster response. In other words, the latency that defines the time required to collect and process data on a network has to be reduced. This is achieved thanks to the fact that the data is processed at the site of its collection, instead of having to wait for its processing in a central platform such as in the cloud. This provides greater benefits to companies.

How is it different from cloud computing?

There is more than one difference between edge computing and the cloud. To begin with, let’s remember that in cloud computing the data is centralized. While edge computing uses miniature data sets distributed to 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 the processing centers and which can be processed locally.

Another difference, no less important to highlight, is the cost and speed . The cloud has higher processing power and lower cost, but the response is not always fast enough as expected. In contrast, edge computing is more expensive, but its response speed is considerably faster . That is to say:

  • Edge computing = higher cost and faster response speed.
  • Cloud computing = lower cost, lower response speed.

 Is it similar to fog computing?

Although in principle these two concepts maintain similarities in that 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 capacities are located. In other words, edge computing focuses on data storage and processing processes, directly on end devices or on the links with other devices that connect them.

On the other hand, fog computing brings these greater capacities to the network level of a local area, which connects the end devices with 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, more than similar, could be considered as necessary complements to guarantee secure information.

What advantages does it bring?

Let’s see 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 because the data is processed in the same place where it is generated . This, as we have said before, encourages a much faster response to the user . Additionally, although the cost of Edge computing is higher at the time of its acquisition,  in the long term it will result in savings thanks to the data processing model.

Thanks to intelligent distributed data storage systems, large sets of IoT data can be analyzed without having to send it to the server room. Which speeds up the decision-making process and allows you to reduce costs. Most likely, even the proliferation of the 5G network does not mean that data collected by cars, drones or autonomous planes is sent to the server room. On the contrary, it allows speeding up data processing.

Better privacy and data management , as data collected by IoT facilities is currently quite vulnerable to theft or forgery. But in the long run, 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 interruption from bringing down the entire network.


by Abdullah Sam
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