Edge Computing vs Fog Computing

Cloud, fog, and edge computing infrastructures are becoming more common in organizations that rely heavily on data. Organizations can use a variety of computer and data storage resources, including the Industrial Internet of Things, with these systems (IIoT). Although cloud, fog, and edge computing appear to be the same thing, they are different layers of the IIoT.

 

In this blog, we'll take a step back and evaluate edge vs fog computing from a larger perspective. We'll look at the differences and similarities between them, as well as some real-world instances, to try to demystify what has become a popular question as businesses of all sizes struggle to figure out where to place their computing resources.

 

It's necessary to understand cloud computing before getting into edge computing vs fog computing. Cloud computing can be defined as computing power made available as an internet service, usually provided by a third party. 

 

Online storage and file management services are a fantastic example (Google Drive is one such service). Your physical device does not actually store your files with these services.

 

Cloud Computing: A Global standard

 

Cloud computing is the practice of delivering on-demand services or resources through the internet, allowing users to obtain seamless access to resources from remote locations without having to invest additional time, money, or labor. Switching to cloud computing instead of creating in-house data centers saves the organization a lot of money in terms of both investment and upkeep. 

 

Clients store data on third-party online workers rather than saving it to a local hard disc on a single PC. A client must first enter a record linked to cloud management in order to access information. Even specialized companies do not have access to the client's information once it has begun to be encrypted. 

 

For the Internet of Things, this means securely storing and managing a large amount of data, as well as having instant access to it from a variety of devices, at any time and from any location.

 

Also Read | Cloud Computing- Public vs Private Cloud
 

What is Fog Computing, and how does it work?

 

Cisco coined the phrase Fog Computing, which is defined as an extension of the cloud computing paradigm from the core to the periphery of the network. Fog computing is an intermediary layer that extends the Cloud layer to bring computing, network, and storage equipment closer to end-nodes in the Internet of Things (IoT). 

 

Fog nodes are edge devices that can be put anywhere with network connectivity, such as alongside railway tracks, traffic controllers, parking meters, and other locations. It is a supplement to cloud computing rather than a substitute. It improves latency while also addressing security concerns while transmitting data to the cloud. 

 

It improves the overall system efficiency by integrating closely with end devices, hence increasing the performance of key cyber-physical systems.

 

The fog nodes either delete or keep the uninteresting data at their end for further processing. As a result, fog nodes verify that cloud storage is free of undesirable data before processing and transferring the data fast.

 

Advantages of Fog Computing

 

Fog computing, as we now know, is a layer that sits between the edge and the cloud. What are the advantages of wearing a second layer? 

 

• The first benefit is increased data traffic efficiency and a reduction in latency. The data that the cloud receives for your individual embedded application is far less crowded when you use a fog layer. 

 

• A cloud may now respond directly to the data it receives from the fog layer, rather than having to sort through a mass of useless data before taking action or returning findings.There are a lot more advantages when you look at the big picture. 

 

• The quantity of storage required for your cloud application would be significantly reduced. Because the cloud would only store and handle relevant data, this is the case. The data transfer would also be speedier. Because the amount of data transported to the cloud is greatly reduced, this is the case.

 

 

What is Edge Computing, and how does it work?

 

The term "Edge Computing" refers to processing in the context of a specific worldview. It provides data about data and electricity closer to the device or information source where it's needed most often.

 

Edge Computing is concerned with dealing with persistent data close to the data source, which is referred to as the organization's 'edge.' Instead of bringing together cloud or data gathering zones, it is connected to running applications as close as feasible to the place where the data is created.

 

It was created as a result of the significant expansion of Internet of Things devices, which work with the web to accept information from the cloud or send data back to the cloud. 

 

Computing takes place at the edge of a device's network under this technology. This simply indicates that the computer is linked to the device's network. The data is subsequently processed and transmitted in real time to the cloud server using this network. The edge computer, also known as an edge node, is the computer that performs this task.

 

The data is instantaneously processed and transferred to the device using this technology. The one catch is that the edge nodes will send any type of data, even if it is of little or no importance. Another technology called fog computing can help with this.

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Arrangement of Devices in Edge and Fog Computing

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Differences between Fog Computing and Edge Computing

 

The following are the differences between fog computing and edge computing:

 

1. Concept

 

Although the basic goals of edge computing and fog computing are similar – namely, to reduce network congestion and end-to-end delay – they differ in how they process and handle data, as well as where the intelligence and processing power is located. 

 

Both concepts are frequently interchanged because they both imply bringing intellect and processing power to the location where data is generated. While processing data at a fog node or an IoT gateway, fog computing pushes intelligence down to the local area network level of the network architecture. 

 

Edge computing embeds the edge gateway's intelligence and power in devices like programmable automation controllers.

 

2. Communication of Data

 

Data communication between data-generating devices and the Cloud environment in Fog Computing involves several steps: initially, communication is routed to the i/o points of a PAC, then through a protocol gateway, which converts data to a comprehensible format. 

 

The data is subsequently sent to a local network Fog node before being sent to the Cloud for storage. On the other hand, communication in Edge Computing is significantly simpler, and there are possibly fewer sources of failure.

 

3. Architecture

 

Fog computing is a decentralized computing infrastructure that extends cloud computing and services to the network's edge, bringing computer, network, and storage devices closer to end-nodes in the Internet of Things. The goal is to boost efficiency while lowering the volume of data sent to the cloud for processing, analysis, and storage. 

 

Edge computing, on the other hand, is a term that predates the term Fog computing. It is a computing architecture that collaborates with end-user clients and one or more near-user edge devices to push computational resources to data sources such as sensors, actuators, and mobile devices.

 

4. Applications

 

Due to the restricted capabilities of the devices that collect data for processing, edge computing is typically utilized in less resource-intensive applications. One such application is predictive maintenance. 

 

Manufacturers can use edge computers in the form of sensors to analyze plant equipment and detect changes before they fail. IIoT sensors continuously monitor equipment health and use analytics to alert users about upcoming maintenance requirements. 

 

Edge devices are also commonly used in healthcare applications such as patient monitoring. Smart glucose meters and heart monitors, for example, connect directly to users' cellphones and send vital data to their healthcare provider in real time. Finally, massively multiplayer online gaming remains popular all over the world. 

 

Because all inputs and processing occur on the edge device, which can be a gaming console, a personal computer, or a smartphone, this is a great illustration of edge computing. Because this type of gaming is so latency-sensitive, just the game session's metadata is sent to the cloud for processing. 

 

The outcomes of all participants' actions are displayed in real-time if the links between the edge devices and the cloud server are reliable. 

 

Fog computing, on the other hand, is frequently used in time-sensitive applications that demand high-volume, resource-intensive data processing from a dispersed network of devices. In the United States and around the world, autonomous vehicles, particularly cars and drones, are rapidly gaining appeal. 

 

These vehicles, which are utilized for both civic and military purposes, generate large amounts of data. This data must be handled in real time, or lives could be jeopardized. 

 

This is why, in order to run efficiently, many autonomous vehicles rely on fog computing. To enable efficient administration, smart grids also necessitate the processing of massive volumes of real-time data. 

 

These applications involve a large number of sensors and other edge devices that are widely spread. As a result, fog computing is used to process data in parallel without slowing down response time. 

 

Finally, data acquired from a large number of edge computers is used in real-time analytics that use artificial intelligence and machine learning to provide actionable business insights. 

 

While long-term analytics can be performed directly on a centralized cloud computer, short-term analytics can be performed using fog computers. This enables time-sensitive data analytics applications, such as those used in the banking and finance industries, to be met.

 

Also Read | Cloud Computing vs Grid Computing

 

Bottom Line: What Role Does Fog and Edge Computing Play in the Future?

 

The Internet of Things is the most common use case for edge and fog computing. This is likely due to the fact that most previous research on the subject has focused on IoT prospects. That, however, may alter as people become more interested in pushing past preconceived boundaries. 

 

Edge and fog computing could also help with the large volumes of data recorded by television cameras during live sporting events. Employ edge computing vs. fog computing successfully now that you know where to use them and how they can bring computer data closer to the source of data. 

 

It will ensure that the data is processed without the need for a central cloud server right away. Both of these approaches are in the early stages of development and will have a wide range of applications in the future