Edge computing is a distributed information technology (IT) architecture. in which data processing and storage are performed closer to the edge of the network, typically at or near the source of data generation. It is a computing infrastructure that bring computation and data storage closer to where it is needed, to improve the performance, reliability, and security of applications and services.
Edge computing is becoming increasingly important as more and more devices are being connected to the internet and generating large amounts of data. It is being used in a variety of industries, including healthcare, manufacturing, transportation, and smart cities, among others.
Instead of sending data to a remote server for processing and analysis, edge computing devices, such as sensors, gateways, or other IoT devices, can perform computation and analysis on the data locally, without the need for an internet connection. This can improve response time, reduce network latency, and alleviate the burden on centralized servers.
In simplest terms, edge computing moves some portion of storage and compute resources out of the central data center
and closer to the source of the data itself. Rather than transmitting raw data to a central data center for processing and analysis, that work is instead performed where the data is actually generated , whether that’s a retail shops, a factories , a utility centres or across a smart city. Only the result of that computing work at the edge,
such as real-time business insights, equipment maintenance predictions or other actionable answers, is sent back to the main data center for review and other human interactions.
Edge computing has a wide range of applications:
Internet of Things: Edge computing can enable real-time data processing and analytics in IoT devices, improving their performance and reducing latency. This can be particularly useful in applications such as smart homes, smart cities, and industrial automation.
Autonomous vehicles: Edge computing can help autonomous vehicles process data in real-time, improving their safety and
responsiveness. This is particularly important in applications such as self-driving cars, with low latency and high reliability.
Video streaming: Edge computing can enable high-quality video streaming by processing video data closer to the end-user, reducing the need for data transmission to central servers. This can improve the user experience and reduce network congestion.
Health: Edge computing can help healthcare providers deliver real-time analytics and insights, improving patient care and reducing cost of unnecessary tests. For example, wearable devices that monitor patient health can use edge computing to process data in real-time and alert healthcare providers in case of emergencies.
Retail: Edge computing can enable real-time inventory tracking and management, improving supply chain efficiency and reducing costs. This can be particularly useful in applications such as e-commerce and logistics.
Overall, edge computing can help organizations improve their operational efficiency, reduce costs, and improve the user experience by enabling real-time data processing and analytics at the edge of the network.
