What is the calculation of the fog? | The comparison

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• What is the calculation of the fog? | The comparison

IT fog refers to a decentralized IT structure, where resources, including data and applications, are placed in logical locations between the data source and the cloud; It is also known as "mist" and "mist net". The goal is to bring basic analytics services to the edge of the network, improving performance by positioning IT resources closer to where they are needed, thus reducing the distance to transport data across the network, thereby improving overall efficiency and network performance. Computer fog can also be implemented for security reasons, as it has the ability to segment bandwidth traffic and introduce additional firewalls into a network for added security. Computer fog has its origins as an extension of cloud computing, which is the paradigm of having data, storage, and applications on a remote server and not hosted locally. With the cloud computing model, the client can buy the services of a provider, which not only provides the service, but also maintenance and updates, with the advantage of being accessible anywhere and facilitating teamwork.

History of fog calculation.

The term fog computing is associated with Cisco, which trademarked the name "Cisco Fog Computing", which was reproducing in cloud computing because clouds are in the sky, and fog refers to clouds. Close to the ground. In 2015, an OpenFog consortium was created with founding members ARM, Cisco, Dell, Intel, Microsoft, and Princeton University, and additional contributing members including GE, Hitachi, and Foxconn. IBM introduced the term closely allied with, and mostly synonymous with (though in some situations not exactly) "edge IT."

Advantages and disadvantages

Calculating fog has a number of advantages. By adding the ability to process data closer to where it was created, Computer Fog seeks to create a lower latency network with less data to download, thereby increasing the efficiency for it to be processed. There is also the advantage that the data can still be processed with the fog calculation in a situation where bandwidth is not available. The IT fog provides an intermediary between these IoT devices and the cloud computing infrastructure they connect to, as it is able to analyze and process data closer to where it came from, filtering what is uploaded to the cloud. One drawback of cloud computing is that all of this network computing is highly dependent on data transport. Although broadband Internet access has generally improved over the past decade, accessibility, congestion spikes, slower speeds on 3G and 4G mobile cellular networks, as well as opportunities Limited Internet availability, whether underground, off-grid or by plane, still presents challenges. This lack of constant access leads to situations where data is created at a rate that exceeds the speed at which the network can move it for analysis. It also raises concerns about the security of this created data, which is becoming more and more common as IoT devices become more and more common. Physically, this additional computing power closest to the data creation site in a fog computing setup is at the level of a fog node, which is considered an essential ingredient of a cloud-based network. foggy thing. The fog node, which is located in a smart router or gateway device, allows the data to be processed in this smart device, so that only the necessary data is transmitted to the cloud and reduces the bandwidth used.

Fog applications in the real world.

An example of a use case for calculating fog is a smart grid. Today's power grids are quite dynamic, responding to increased electricity consumption and reducing production when it is not necessary to be economical. To function efficiently, a smart grid relies heavily on real-time data on electricity production and consumption. Fog calculation is ideal for this, because in some cases the data is created in a remote location and it is better to process it there. In other situations, the data does not come from an isolated sensor, but from a group of sensors, such as electric meters in a neighborhood, and it is better to process and aggregate the data locally, rather than overload the data rate by transmitting the data without process in full. Another use case for fog computing relates to IoT applications, such as the next-generation smarter transportation network, known as V2V in the United States, and the Car-to-Car consortium in Europe. . Dubbed the ``Internet of Vehicles,'' every vehicle and traffic enforcement device is an IoT device that generates a stream of data and connects to other vehicles, as well as traffic lights and the streets themselves, with the promise of a safer transport for a better collision. avoidance with smoother traffic. Every vehicle has the potential to generate a certain amount of data just about speed and direction, as well as transmit to other vehicles when and how much it brakes. Since the data comes from moving vehicles, it must be transmitted wirelessly on the 5.9 GHz frequency in the United States; If not done correctly, the amount of data could easily overwhelm your finished mobile bandwidth. A key element in sharing limited mobile bandwidth is vehicle-level data processing through a fog calculation approach via an on-vehicle processing unit. Fog computing has also been applied to manufacturing in the IIoT (Industrial Internet of Things). This allows manufacturing devices connected with sensors and cameras to collect and process data locally, instead of sending all that data to the cloud. Local processing of this data, in a real-world wireless model, resulted in a 98% reduction in transmitted data packets, while maintaining 97% data accuracy, in a fog computer model of distributed data. Plus, Power Save is ideal for efficient power consumption, a crucial feature in setting up battery-powered devices. Although IT fog is a more recent development in the cloud computing paradigm, it has significant momentum and is well positioned for growth.