Understand Edge Computing

▎Delving into Edge Computing

Edge computing refers to the practice of performing computations in close proximity to the source of data or the end-users, diverging from the conventional model that relies on centralized data centers or cloud infrastructure. This approach is particularly advantageous for applications that demand minimal latency and for the efficient handling of data generated by local IoT devices, thereby facilitating swift, data-informed decision-making.

▎What constitutes edge computing?

Contrasting with the standard cloud computing paradigm, where resources and services are housed in massive, centralized datacenters accessible to end-users throughout an organization, edge computing shifts the focus towards positioning computational power in closer quarters to the physical devices or data sources, effectively at the network's "edge."

The strategy of situating computational services nearer to edge locations or devices offers users the advantage of expedited and more dependable services, while businesses gain from the enhanced capacity to process data rapidly and maintain applications with minimal concern for latency.

▎What defines an edge device?

Edge devices encompass a range of physical hardware such as IoT gateways, industrial controllers, intelligent screens, point-of-sale systems, vending machines, robotic systems, and unmanned aerial vehicles. Positioned in remote network locales, these devices possess sufficient memory, processing capabilities, and computational resources to gather data, analyze it, and act on the insights with near real-time efficiency, requiring minimal support from other network segments. Often, an organization may operate a vast network of edge devices, all of which can be overseen and managed from a single, centralized command point.