Cloud computing vs fog computing vs edge computing: The future of IoT

prk-admin 1400/06/20
Cloud computing vs fog computing vs edge computing: The future of IoT

Unfortunately, nothing is spotless, and cloud technology has some drawbacks, especially for Internet of Things services. Plus, there’s no need to maintain local servers and worry about downtimes – the vendor supports everything for you, saving you money. PaaS – A development platform with tools and components to build, test, and launch applications. This article aims to compare Fog vs. Cloud and tell you more about Fog vs. cloud computing possibilities and their pros and cons.

Moving raw data across a public network can place that data at risk and potentially compromise the organization’s compliance posture. Retaining data on-site or vastly reducing the distance that data needs to travel can shrink the potential attack surface for data snooping or theft. In addition, minimizing the amount of raw data exposed to a public network can potentially improve compliance, as long as the data is adequately secured at the edge or in fog nodes. The data ingestion specialist’s latest platform update focuses on enabling users to ingest high volumes of data to fuel real-time… Federal agencies are clearly moving to the cloud and are also increasingly adopting edge computing solutions. The reason being that cloud is at a distance from the point of origin whereas, in fog computing, it analyzes and reacts to the data in less than a second.

The data is first processed locally, and only then sent to the main storage. In turn, cloud computing services providers can benefit from significant economies of scale by delivering the same services to a wide range of customers. We have previously mentioned that fog computing is an enhancement of the cloud version.

Cloud computing is the most widely-used form of IoT data management. There are any number of potential use cases for fog computing. One increasingly common use case for fog computing is traffic control. Because sensors — such as those used to detect traffic — are often connected to cellular networks, cities sometimes deploy computing resources near the cell tower.

fog computing vs cloud computing

Fog computing is a mediator between hardware and remote servers. It regulates which information should be sent to the server and which can be processed locally. In this way, fog is an intelligent gateway that offloads clouds enabling more efficient data storage, processing and analysis. The cloud improves communication between devices and applications, quickly sending data between data centers and local nodes. Fog acts as a middle layer between cloud and edge and provides the benefits of both. It relies on and works directly with the cloud handing out data that don’t need to be processed on the go.

Real-Time Analysis

Cloud computing service providers can benefit from significant economies of scale by providing similar services to customers. Want to monitor your Nutanix infrastructure performance, security, and availability? Here we reveal some best monitoring software for Nutanix to keep your data safe and secure. Smart cities need cloud computing to offer an interactive and effective experience to their residents.

  • By using cloud computing users can access the services from anywhere whenever they need.
  • Devices such as smart glucose monitors and heart monitors connect directly to patients’ smartphones and relay relevant information to their healthcare provider in real-time.
  • These platforms work together to process data locally, even in environments where bandwidth is severely restricted or connectivity is unreliable.
  • Rather, the edge computer is a device that stores and computes data and is connected to the data-generating device over a local area network.
  • Cloud architecture is centralized and consists of large data centers that can be located around the globe, a thousand miles away from client devices.
  • Remember, the goal is to be able to process data in a matter of milliseconds.
  • In fog computing, data is received from IoT devices using any protocol.

Soldiers’ vests can also have computing nodes on them to communicate between soldiers and also back to their base in a fog hierarchy. A drone may be trying to land in a particular area, but in order to get clearance to do so, its sensors need to be scanned and verified by a fog computing node, he says. If the drone passes the verification, it will be allowed to fly in and land. By pushing computation, especially AI algorithms and analytics, deeper into the network closer to IoT devices , agencies can decrease their vulnerability, he notes. Like edge, fog computing is still relatively nascent in government. The National Institutes of Standards and Technology in March 2018 produced a document that describes a conceptual model of fog computing but does not definitively define it.

Difference Between Cloud Computing and Fog Computing

The new technology is likely to have the greatest impact on the development of IoT, embedded AI and 5G solutions, as they, like never before, demand agility and seamless connections. Finally, if there is no internet connection, the cloud becomes inaccessible. Fog technologies apply dozens of protocols to avoid system failure, maximizing availability globally. You could say that it is a very good enhancement to cloud computing that generates a better user experience. Fog computing vs. edge computing — while many IT professionals use the terms synonymously, others make subtle but important distinctions between them.

fog computing vs cloud computing

Fog computing has low latency and provides a high response rate and has become most recommended compared to cloud computing. It supports the Internet of Things as well as compared to Cloud Computing. The good thing for the users is fog and cloud computing can complement each other. By blending these two solutions, you can create new communication and experiences. Especially for IoT architecture, both computing models play crucial roles. Since these are getting increasingly popular, knowing the difference between fog and cloud computing is essential for business decisions and deployment.

Key Differences Between Cloud Computing and Fog Computing

The relevant data gets stored in the cloud, while the irrelevant data can be deleted, or analyzed at the fog layer for remote access or to inform localized learning models. Cloud-level fog computingruns on servers or appliances located in the cloud. These devices can be used to process data before it is sent to end users. Edge-level fog computingruns on servers or appliances located at the edge of a network. These devices can be used to process data before it is sent to the cloud. The main difference between fog computing and cloud computing is that Cloud is a centralized system, whereas Fog is a distributed decentralized infrastructure.

fog computing vs cloud computing

Microsoft has stated data drift to be one of the top reasons model accuracy degrades over time. Cost efficiency – A significant reduction in operational costs. With 5+ years of mechanical engineering experience, he’s passionate about all things engineering and tech. He also loves bringing engineering down to a level that everyone can understand. Ryan lives in New York City and writes about everything engineering and tech. AR/VR — enabling low-latency, high-quality augmented and virtual reality experiences.


If there is no fog layer, the cloud communicates with devices directly, which is time-consuming. Even knowing the difference between cloud, fog and edge computing, it can be challenging to figure out which approach to pick and how to extract real benefits from it. The technology landscape for IoT and big data has been changing rapidly in the last several years. Adoption of cloud and other forms of computing for IoT requires skills and expertise. Edgeis the closest you can get to end devices, hence the lowest latency and immediate response to data. This approach allows to perform computing and store some volume of data directly on devices, applications and edge gateways.

fog computing vs cloud computing

Fog computing cascades system failure by reducing latency in operation. It analyzes the data close to the device and helps in averting any disaster. Cloud has different parts such as frontend platform (e.g., mobile device), backend platform , cloud delivery, and network . Cloud computing receives and summarizes data from different fog nodes. Some of the tools and services to help your business grow.

Fog computing vs. edge computing

It increases cost savings as workloads can be transferred from one Cloud to another cloud platform. Cloud users can quickly increase their efficiency by accessing data from anywhere, as long as they have net connectivity. It works on a pay-per-use model, where users have to pay only for the services they are receiving for a specified period. Fog computing uses different protocols and standards, so the risk of failure is very low. Fog does short-term edge analysis due to the immediate response, while Cloud aims for a deeper, longer-term analysis due to a slower response. On the other hand, Cloud servers communicate only with IP and not with the endless other protocols used by IoT devices.

Edge and fog computing are less known than cloud but have a lot to offer to businesses and IoT companies in particular. These networks solve many issues that can’t be solved by IoT cloud computing services and adapt the decentralized data storage to particular needs. Let’s fog vs cloud computing examine the benefits of edge, fog and cloud computing individually. Fog computing is useful when the Internet connection isn’t always stable. For instance, on connected trains, fog can pull up locally stored data in areas where the Internet connection can’t be maintained.

Cloud Computing Use Cases in IoT

With cloud computing, you can scale up and down the resource and infrastructure usage according to your requirements. Using fog computing means no complaints about the loss of connection. It uses multiple interconnected channels to ensure the best connectivity for any activity. In many cases, data collection and processing occur on the same device, such as on an endpoint computer or IoT device. IoT development and cloud computing are among the core competencies of SaM Solutions. Our highly qualified specialists have vast expertise in IT consulting and custom software development.

Why Is Fog Computing Beneficial for IoT?

Right now, cloud, fog and edge technologies provide irreplaceable solutions to many Internet of Things challenges. Let’s take a look at some future possibilities for Internet of Things and different computing technologies. Cloud, edge and fog computing are often talked about in conjunction with IoT because these technologies support each other. Internet of Things relies on different data management services to store and analyze IoT device data and metrics, enable automation, etc. Many companies focus on edge computing on their way to decentralization, whereas others adopt fog computing as a main data storage system due to its high speed and increased availability.

This feature is highly beneficial for companies with a hybrid or remote team. Fog computing is a part of cloud computing, and hence, these are interconnected. In the natural world, you will see that fog stays closer to the earth than clouds. However, depending on the scale of operations and the quality of the components used, it is usually more economical for edge computing requirements to be outsourced. Here, edge computers in the form of sensors help manufacturers analyze plant equipment and detect changes before a failure occurs. IIoT sensors constantly monitor equipment health and use analytics to warn of impending maintenance needs.

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