Much is said about the new technologies that are flooding our daily lives. In fact, the concept of cloud computing is no longer isolated. New models appear every day with the intention of decentralizing and streamlining processes. Fog computing is part of those new models that seek to leave centralized computing in the past and bets on distributed or local computing that advances hand in hand with what we now call the Internet of Things (IoT) .
While some people believe that centralized computing is far better than local, and that distributed systems will never offer the same efficiency as a clean cloud infrastructure, there is no doubt that interest in Fog computing is generating excitement and growing. . As IoT evolves, the fog will support its power. But what exactly does this term actually mean? Does fog computing have the potential to replace cloud computing?
What is fog computing?
Fog computing also known as fog computing or fogging ; It is a model of distributed or decentralized computing in which the processing and storage of data is not carried out in the cloud, but outside it . At the edge of the network much closer to where the data originates. In order to obtain greater efficiency and streamline processes by decongesting the cloud and sending faster responses to users.
Fog computing can also be defined as a set of low-level processes that take place near a data source on a specific network. Application resources and services are placed where they are needed to reduce the amount of data sent to the cloud for processing and storage. So smart devices can use the computing that is closest to their place on the network. In this way, better results can be obtained.
Cloud computing can even be considered part of the cloud, since it basically extends the computing capabilities and services of the cloud. To the edge of the network, bringing all these benefits to the place where data is generated and processed locally. This decentralized approach to the web is becoming increasingly popular thanks to the Internet of Things (IoT). Its ultimate goal is efficiency, improving performance by reducing the amount of data sent to the cloud.
Characteristics of fog computing
Fog computing as well as each of the models of computing based on IoT or IT. It has certain characteristics of its own, let’s see 3 of them:
Low latency and location awareness: in fog computing, processes are carried out outside the cloud, in the same place where the data is generated or very close to it. This allows to considerably reduce the analysis and data processing times, resulting in a quick response. Facilitating in this way that decisions can be made quickly and assertively at the precise moment in which it is required.
High number of nodes – So- called fog nodes function as intelligent computing and switching nodes. They form a connecting component between end devices and the cloud with their own intelligence . These fog nodes decide which data will be processed decentrally and which will be sent to the data endpoints in the central cloud. Since the main objectives of fog computing are to shorten communication paths and reduce the volume of data in the cloud.
Another feature that can also be taken as functionality is the fact that in fog computing an internet connection is not essential. Since the processes are carried out on the local network and on the same device where the data is generated, it is not necessary to access the cloud for its capture and processing. This allows the programs and applications contained in the device to be used in the same way and can be updated when the connection is recovered.
How is it different from edge computing?
The difference between these two models lies in the place where the data development and storage processes take place . Well, although the two coincide in carrying out these activities outside the cloud and as close as possible to where the data is generated, they differ in the very location where these processes take place. Thus, while for Edge computing the data development and storage processes must be carried out on the same end devices.
Fog computing contemplates this same data processing at the edge, but at the network level of a local area that is responsible for connecting with the end devices and the cloud. In other words, computing in the fog contemplates carrying out its processes in the network that connects the cloud with the end devices where the data is emitted. And edge computing or edge computing guides the performance of these processes directly on the end devices.
What applications does it have?
Fog computing has varied applications in industry and is gaining more ground every day. For example: Manufacturing machines and logistics systems communicate with each other and coordinate their work processes independently. Humans intervene as little as possible. That’s the vision behind the term “smart factory.” The amount of data that is generated must be processed locally due to the aspect of time. For this reason, fog computing is used as a solution.
Autonomous or semi-autonomous vehicles are another application area for fog computing. The intelligent vehicle requires a great deal of information about its surroundings and its drive technology. These are supplied to you by various sensors and must be analyzed and processed in a very short time so that the vehicle can react in real time to the traffic situation and unexpected events. Fog computing allows data to be processed directly on the vehicle.
Another area of application could be intelligent traffic control with the help of cameras. “Smart cameras” monitor the flow of traffic, recognize emergency vehicles with flashing lights and change a green wave through them. The data is analyzed in situ and the reaction starts immediately. In this way, the signs can be changed immediately if necessary and other actions can be carried out that could not be carried out on time if it were not for the computation in the fog.
What advantages does it bring?
Fog computing has several advantages over classic cloud computing. Some of the key benefits are briefly summarized below:
- Latency and processingtimes are reduced, meaning that the waiting times for response and data processing are considerably reduced.
- The volume of data to be transferred to the cloud is reduced. Fog computing classifies which data to send to the cloud and which data it can process directly.
- Cloud traffic is reduced, reducing the amount of data that is sent avoids congestion that slows down processes in the cloud.
- Even if the network connection is interrupted, IoT devices can continue to function without restrictions
- Sensitive data does not have to leave the place where it was created.
- Analysis and decision-making processes are accelerated. By carrying out the processes in the same place where the data is generated, faster responses are issued.