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Difference Between Edge Computing and Fog Computing

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Cloud computing refers to the on-demand delivery of IT services/resources over the internet. On-demand computing service over the internet is nothing but cloud computing. By using cloud computing users can access the services from anywhere whenever they need.

Nowadays, a massive amount of data is generated every second around the globe. Businesses collect and process that data from the people and get analytics to scale their business. When lots of organizations access their data simultaneously on the remote servers in data centers, data traffic might occur. Data traffic can cause some delay in accessing the data, lower bandwidth, etc. But cloud computing technology alone is not effective enough to store and process massive amounts of data and respond quickly.  

For example, in the Tesla self-driving car, the sensor constantly monitors certain regions around the car. If it detects an obstacle or pedestrian on its way, then the car must be stopped or move around without hitting. When an obstacle is on its way, the data sent through the sensor must be processed quickly and help the car to detect before it hits. A little delay in detection could be a major issue. To overcome such challenges, edge computing and fog computing are introduced.  

Edge and Fog Computing

Edge and Fog Computing

Edge Computing

Computation takes place at the edge of a device’s network, which is known as edge computing. That means a computer is connected with the network of the device, which processes the data and sends the data to the cloud in real-time. That computer is known as “edge computer” or “edge node”.  

With this technology, data is processed and transmitted to the devices instantly. Yet, edge nodes transmit all the data captured or generated by the device regardless of the importance of the data.  

Example of Edge computing:

  • Autonomous vehicle edge computing devices collect data from cameras and sensors on the vehicle, process it, and make decisions in milliseconds, such as self-parking cars.
  • In order to accurately assess a patient’s condition and foresee treatments, data is processed from a variety of edge devices connected to sensors and monitors.

Here Fog Computing was introduced and becomes an ideal solution.  

Fog Computing

Fog computing is an extension of cloud computing. It is a layer in between the edge and the cloud. When edge computers send huge amounts of data to the cloud, fog nodes receive the data and analyze what’s important. Then the fog nodes transfer the important data to the cloud to be stored and delete the unimportant data or keep them with themselves for further analysis. In this way, fog computing saves a lot of space in the cloud and transfers important data quickly.  

Difference Between Edge Computing and Fog Computing




01.Less scalable than fog computing.Highly scalable when compared to edge computing. 
02.Billions of nodes are present. Millions of nodes are present. 
03.Nodes are installed far away from the cloud. Nodes in this computing are installed closer to the cloud(remote database where data is stored).
04.Edge computing is a subdivision of fog computing.Fog computing is a subdivision of cloud computing. 
05.The bandwidth requirement is very low. Because data comes from the edge nodes themselves. The bandwidth requirement is high. Data originating from edge nodes is transferred to the cloud.  
06.Operational cost is higher.Operational cost is comparatively lower.
07.High privacy. Attacks on data are very low. The probability of data attacks is higher. 
08.Edge devices are the inclusion of the IoT devices or client’s network. Fog is an extended layer of cloud. 
09.The power consumption of nodes is low. The power consumption of nodes filter important information from the massive amount of data collected from the device and saves it in the filter high. 
10.Edge computing helps devices to get faster results by processing the data simultaneously received from the devices. Fog computing helps in filtering important information from the massive amount of data collected from the device and saves it in the cloud by sending the filtered data. 

Last Updated : 22 Nov, 2022
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