For IoT Projects, Fog Computing vs. Cloud Computing
According to Statista, there will be 30 billion IoT devices on the planet by 2020, and 75 billion linked objects by 2025. All of these devices can generate massive quantities of data that must be processed rapidly and sustainably. Fog computing, like cloud computing, enters the picture to meet the rising demand for IoT solutions. Fog is much better in some thin environments. The goal of this article is to compare fog vs. cloud computing and to inform you about the advantages and disadvantages of each.
We’ve all heard of the word “cloud,” which refers to a network of various devices, computers, and servers linked through the Internet.
A computer device like this can be divided into two sections metaphorically:
Wireless connections enable these two layers to communicate directly with one another.
Cloud computing technology offers a variety of services that can be divided into three categories:
IaaS (Infrastructure as a Service) is a virtual data centre that provides data storage, computing power, and networking.
PaaS (Platform as a Service) is a development platform that includes tools and components for developing, testing, and deploying apps.
Ready-made applications customised to a variety of business needs is known as SaaS (Software as a Service).
Also see: What’s the Difference Between IaaS, PaaS, and SaaS?
When you link your business to the cloud, you gain access to the aforementioned resources from any place and on a variety of devices. As a result, the biggest advantage is accessibility.
Furthermore, you won’t have to worry about maintaining local servers or dealing with downtimes because the vendor will take care of it for you, saving you money.
Integrating the Internet of Things with the cloud is a cost-effective method of doing business.
Off-premise networks provide the scalability and versatility needed to handle and analyse data collected by connected devices, while specialised platforms (such as Azure IoT Suite, IBM Watson, AWS, and Google Cloud IoT) empower developers to build IoT apps without large upfront hardware and software investments.
Pros of Cloud for IoT
Since connected devices have limited storage space and processing power, cloud computing integration comes in handy:
Improved output — IoT sensors and data processing systems communicate more quickly.
Storage capacities — a large volume of data can be integrated, aggregated, and shared thanks to highly scalable and limitless storage space.
Processing power — on-demand virtual processing power is available from remote data centres.
Cost savings — licencing fees are less expensive than the cost of on-premise facilities and ongoing repairs.
Cons of Cloud for IoT
Unfortunately, nothing is perfect, and cloud technology, particularly for Internet of Things services, has some drawbacks.
High latency — it’s becoming more and more common. Because of the gap between client devices and data processing centres, IoT apps require extremely low latency, which the cloud cannot provide.
Downtime — it’s becoming more and more common. Because of the gap between client devices and data processing centres, IoT apps require extremely low latency, which the cloud cannot provide.
Security and privacy — the personal information is transmitted over globally linked networks alongside thousands of gigabytes of information from other users; it’s no wonder that the infrastructure is vulnerable to cyber attacks or data loss; the issue can be partly solved with the aid of hybrid or private clouds.
Fog is a cloud computing extension that consists of several edge nodes that are directly connected to physical devices, according to the description.
As opposed to centralised data centres, such nodes are physically closer to devices, allowing them to have instant connections. Edge nodes’ high processing capacity enables them to process large amounts of data without sending it to distant servers.
Fog may also include cloudlets, which are small but efficient data centres located at the network’s edge. Their aim is to help resource-intensive IoT apps with low latency requirements.
Fog computing differs from cloud computing in that the cloud is a centralised system, while fog is a distributed decentralised infrastructure.
Fog computing is a form of computing that acts as a bridge between hardware and remote servers .It controls which data should be sent to the server and which should be processed locally .Fog serves as an intelligent portal that offloads cloud workloads, allowing for more efficient data storage, processing, and analysis.
Fog networking is not a different architecture, and it does not replace cloud computing; rather, it complements it by getting as close as possible to the source of information.
Pros of Fog Computing
The most significant effect of the new technologies is likely to be on the growth of IoT, embedded AI, and 5G solutions, as they demand agility and seamless connections like never before.
There are no latency issues because data is aggregated at various points rather than being sent all at once to a single location through a single channel.
Due to the many interconnected networks, a loss of communication is unlikely.
Since data is processed by a large number of nodes in a complex distributed system, there is a high level of protection.
Improved user experience — fast answers and no downtime keep users happy.
Low latency — since fog is geographically closer to users, it can react quickly.
Power-saving protocols, such as Bluetooth, Zigbee, and Z-Wave, are used by edge nodes.
The Drawbacks of Fog Computing
While there are no obvious drawbacks to the technology, there are a few flaws to be aware of:
Fog is an extra layer in the data processing and storage system, making it a more complex system.
Additional costs — businesses should purchase edge devices such as routers, hubs, and gateways.
Fog’s scalability is limited compared to the cloud.
The Differences Between Fog Computing and Cloud Computing
The definitions of cloud and fog are somewhat similar. On certain criteria, however, there is a distinction between cloud and fog computing. The following is a side-by-side analysis of fog computing and cloud computing.