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Edge computing processes data and runs applications close to where data is generated or requests are made, reducing latency compared with centralized cloud processing.
Edge computing is a distributed computing model that moves computation, data storage, and application services closer to the sources of data and end users, rather than relying entirely on centralized cloud data centers. By processing requests at nearby edge servers, gateways, devices, or micro data centers, it reduces network latency, bandwidth usage, and response times. The concept developed from content delivery networks in the 1990s and later expanded to support broader applications and Internet of Things (IoT) services. Edge computing is especially valuable for applications requiring rapid or continuous responses, such as autonomous vehicles, smart cities, industrial systems, augmented reality, facial recognition, cloud gaming, and real-time IoT management. It can improve responsiveness, efficiency, privacy, and service continuity during connectivity problems, although it also introduces challenges involving security, scalability, device heterogeneity, distributed management, and reliability. Fog computing may overlap with edge computing or serve as an intermediate layer between edge infrastructure and the cloud in larger deployments.
Edge computing processes data and runs applications close to where data is generated or requests are made, reducing latency compared with centralized cloud processing.
It helps reduce bandwidth consumption and improve responsiveness for real-time applications such as IoT, autonomous driving, augmented reality, cloud gaming, and smart cities.
Processing data locally can improve privacy and allow services to continue during cloud or Internet outages, but distributed edge systems require specialized security, scalability, and reliability management.
A distributed computing model that places computation and data storage near data sources and end users to reduce latency and network traffic.
A nearby device, server, gateway, or micro data center that performs computation or provides services at the network edge.
A model in which computing resources and data storage are provided through centralized or remote data centers over a network.
A distributed computing layer that may operate between edge devices and centralized cloud infrastructure, especially in larger deployments.
The time required for data or a request to travel between a device and the system processing it.
The deployment of artificial intelligence models on or near the devices where data is collected, enabling faster and more local processing.
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