Grid Computing
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Edge Devices: Physical hardware that performs local data processing, including IoT devices, sensors, and gateways, enabling faster responses by reducing the need to send all data to centralized servers.
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Microservices/Applications: Lightweight, decentralized applications or services running on the edge, allowing for specific tasks like data filtering, analytics, or real-time processing close to the data source.
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Data Processing: Focused on processing data locally at the edge to reduce latency and network bandwidth. This can involve real-time data analysis, filtering, and decision-making without needing to reach the cloud or data center.
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Network Architecture: The design of the network that supports efficient data transfer between edge devices, microservices, and centralized data centers, optimized for low-latency, high-availability communications.
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Security: Implementing strong security protocols at the edge, including device authentication, data encryption, and securing both data at rest and in transit to protect against breaches and ensure privacy.
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Management and Orchestration: Tools for deploying, monitoring, and maintaining edge infrastructure. This involves handling distributed computing environments with automated updates, resource management, and performance monitoring.