Why Fog Computing is Critical to Organizations

Why Fog Computing is Critical to Organizations

Enterprise Networking Mag | Wednesday, October 20, 2021

Since its beginnings, fog computing has evolved. Fog computing is viewed as a requirement for IoT and 5G, embedded artificial intelligence (AI), and 'advanced dispersed and networked systems.'

FREMONT, CA: As a result of the evolution of IoT devices, a vast amount of data was generated. These data sets require a significant amount of bandwidth. Fog computing was developed in response to cloud computing's inability to meet these needs. However, it is not regarded as a substitute for cloud computing. Instead, it was created holistically to address all of the cloud's technical challenges. Fog computing enables users to access data quickly and efficiently. In a nutshell, it assists them in managing, accessing, analyzing, and storing all of their data. While it provides several benefits to the IT infrastructure, it also has a slew of disadvantages. Mainly as a result of their decentralized nature. Understanding the benefits can assist them in determining if it is appropriate for their organization.

Privacy: Fog computing can be utilized to limit the amount to which one's privacy is compromised. Sensitive user data can be evaluated locally rather than being transmitted to a centralized cloud infrastructure. In this manner, the IT team will be able to follow and operate the gadget. Additionally, any subset of data that requires analysis can be transferred to the cloud.

Security: Fog computing enables the connection of various devices to a single network. As a result, operations take place at multiple endpoints rather than in a single area. This allows the detection of possible threats before they affect the entire network.

Productivity: If the customer wishes to customize the machine's operation, they can use fog applications. With the correct set of tools, developers may create these fog apps. Then, after development is complete, it can be deployed whenever the developer desires.

Bandwidth: The bandwidth required for data transmission might be costly, depending on the available resources. Since selected data can be processed locally rather than sent to the cloud, bandwidth needs are meager. This bandwidth reduction will be especially advantageous as the number of IoT devices grows.

Latency: Another advantage of processing selected data locally is the resulting reduction in latency. The data can be processed at the geographically closest data source to the user. This can result in instant responses, which is very beneficial for time-sensitive services.

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