The concept works with the processing of data closer to the source. See below, what is edge computing, what this model of processing technology is based on, the main advantages and points of attention. Everything revolves around decentralizing the computational work of the main data center.
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On the border
Escape from the literal translation, edge computing would be something like edge computing; This is because the data is processed close to the limit of the system's reach, where the most interested parties, the users, are located and have access to faster responses without the constant need to traffic raw data to the data center main system.
edge computing moves a portion of the storage and processing resources away from the main data center and closer to the source of the data itself.
Instead of transmitting raw data for processing and analysis, this work is done where the data is actually generated—whether it's a retail store, a factory floor, an expanding utility, or a a smart city.
Only the output of this edge computing work, such as real-time business insights, equipment maintenance forecasts, or other crucial information, is sent back to the main data center for review and human interactions. Reducing processes and improving transfer speed.
How edge computing works
edge computing is a matter of localization. In traditional corporate computing, data is produced on a client terminal, such as a user's computer. They are moved over a WAN, such as the Internet, through the corporate LAN, where data is stored and handled by a corporate application.
The results of that work are then transmitted back to the client terminal. This remains a proven and time-tested approach to “client-server” computing in most typical business applications.
The number of devices connected to the Internet and the volume of data produced by them and used by businesses is growing too fast for traditional data center infrastructures to absorb.
IT architects have shifted focus from the central data center to the logical frontier of the infrastructure — taking storage and computing resources from the data center and moving them to the point where the data is generated.
Advantages Edge Computing
- Autonomy: This is useful when connectivity is unreliable or bandwidth is constrained due to the environmental characteristics of the site. By processing data locally, the amount to be sent can be greatly reduced, requiring much less bandwidth or connectivity time;
- Data protection: edge computing can be used to keep data close to its source and within the confines of data protection laws. This allows raw data to be processed locally, protecting any sensitive data before sending anything to the cloud or primary data center, which may be in other jurisdictions;
- MonSecurity: Provides an additional opportunity to implement and ensure data security. Any data that crosses the network back to the cloud or data center can be protected by encryption, and the edge computing deployment itself can be hardened against hackers and other malicious activities. .
Points of attention and limitations
- Limited capacity: the implementation of an infrastructure edge computing can be effective, but the deployment model and purpose must be clearly defined. Even extensive deployments of edge computing serve a specific purpose on a predetermined scale using limited resources and few services;
- Connectivity: even overcoming typical network limitations, the deployment of the most tolerant system will require some minimum level of connectivity. One needs to design one that supports poor or erratic connectivity and considers what happens in the local processing area when connectivity is lost;
- Security: It is vital to design a edge computing which emphasizes proper management of devices, such as the application of configuration based on “policies and rules”, as well as security in computing and storage resources: patching and software updates, among others — with special attention to data encryption in rest and on the go.