What is cloud computing?
Cloud computing is an approach for delivering IT resources and services over the Internet. Instead of local servers and data centers, companies, organizations, and individuals use cloud infrastructure to access a wide range of services, resources, and applications. These services are provided by cloud service providers and can be used as needed, creating a flexible and scalable IT infrastructure.
As part of cloud computing, access is thus separated from actual ownership: Many components now exist as a bookable service and are no longer dependent on a physical presence at the location of the organization or company.
In a world where a wide variety of devices and Things are equipped with communication skills and guarantee the exchange of information with as little latency as possible, there is a real need for cloud computing: In order to maintain the imagery of nature, the veil of clouds enthroned above everything must be close to the earth. A rising fog is the result: Fog Computing.
What is fog computing?
Fog computing refers to a decentralized computing infrastructure that brings resources and services closer to the edge of the network, closer to where data is generated, rather than exclusively processing it in remote data centers. The term Fog Computing was used by Cisco and the Open Fog Consortium coined to describe the idea that fog as opposed to Cloud lies closer to the ground and plays around everything lying in it.
In the context of the Internet of Things (IoT) and connected devices, fog computing allows data to be processed closer to devices and sensors instead of sending all data to a central location (i.e. the cloud). This can help reduce latency, use bandwidth more efficiently, and improve overall application performance.
In essence, fog computing extends the idea of cloud computing architecture by bringing an additional layer of resources and services close to end devices. This is particularly useful in applications that require real-time processing, low latency, and high reliability, such as industrial automation, healthcare, autonomous transportation, and other IoT scenarios.
The concept of fog computing is often confused with that of edge computing. There are small but subtle differences between the two designs.
The differences between fog and edge computing as the successor to cloud computing
Although fog computing and edge computing are closely interrelated concepts that are often considered synonymous, they still have some differences. Both approaches aim to bring data processing closer to where the data is generated in order to reduce latency and improve performance. The following is about the main differences and connections between fog computing and edge computing:
- Location of resources:
Edge computing: Focuses on placing resources (computing power, storage, etc.) closer to the devices, usually directly on the devices or in their immediate vicinity.
Fog computing: Expands the idea of edge computing by placing resources not only on the devices but also on network nodes near the devices.
- Hierarchy and scalability:
Edge computing: View each endpoint as a separate entity without emphasizing a hierarchical structure. It is focused on individual devices or local clusters.
Fog computing: Provides a hierarchical structure in which resources are distributed across network nodes. This allows for greater scalability and flexibility as multiple edge devices can be connected to a fog node.
- Processing level:
Edge computing: Often focuses on local, device-based processing to process data right at the source.
Fog computing: Provides an additional processing layer across edge devices to process data closer to network endpoints. It can be seen as an extension of edge computing.
- Areas of use:
Edge computing: Often used in conjunction with IoT devices, sensors, and industrial applications.
Fog computing: Often used in larger network environments, such as smart cities, intelligent transportation systems, and within large IoT infrastructures.
Overall, fog computing is often seen as an extension of edge computing that provides additional layers for a hierarchical distribution of resources and services, while edge computing is more focused on local processing on the device. Both approaches help improve the performance and efficiency of applications in the context of the Internet of Things (IoT) and improve connected devices.
Conclusion on the future of decentralized data use — From cloud computing to fog computing
It's a veritable truism, but the cloud (and cloud computing) is not the final computing blueprint! Fog computing will also be replaced by new paradigms sooner or later. It remains to be seen whether the natural imagery can otherwise be carried on. With regard to the communicative present, emphatically decentralized use of data is itself a successful model that will certainly see some more spurts of innovation.
