The concept of fog computing was developed to combat the latency issues that affect a centralized cloud computing system. The boom of consumer and commercial IoT devices and technologies has put a strain on cloud computing resources. By Jose Gomez.
Fog computing can optimize data analytics by storing information closer to the data source for real-time analysis. Data can still be sent to the cloud for long-term storage and analysis that doesn’t require immediate action. Let’s get a better understanding of the underlying principles behind fog computing and see the ways it can benefit large, dispersed networks.
The article main content:
- How does it work?
- The benefits of fog computing
- The disadvantages of fog computing
- What industries rely on fog computing?
With the sheer amount of data being collected by IoT devices, many organizations can no longer afford to ignore the capabilities of fog computing, but it is also not wise to turn your back on cloud computing either
In reality, any device with computing, storage, and network connectivity can act as a fog node. When data is collected by IoT devices and edge computing resources, it is sent to the local fog node instead of the cloud. Utilizing fog nodes closer to the data source has the advantage of faster data processing when compared to sending requests back to the data center for analysis and action. In a large, distributed network, fog nodes would be placed in several key areas so that crucial information can be accessed and analyzed locally. Good read!
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