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Servers, storage, databases, and software are among the computing services that cloud computing offers online.
Data processing and storage in centralized centers are eliminated, offering economical, expandable, and adaptable solutions. Examples include AWS, Azure, and Google Cloud.
Instead of employing centralized data centers, edge computing processes data near to where it is generated.
Decentralized architecture near data sources reduces latency and bandwidth, enabling real-time processing and analysis. Examples include IoT devices and edge servers.
– Centralized data centers. – Long-distance data transmission. – Higher latency.
– Distributed architecture. – Data processed locally. – Lower latency. – Reduced bandwidth usage.
– Large-scale data storage. – Batch processing. – Web applications.
– IoT devices. – Real-time analytics. – Low-latency applications.
– Scalability – Accessibility – Cost-effectiveness – Centralized management
Reduced latency boosts application response, bandwidth optimization reduces data transmission, reliability ensures operation without network, and enhanced security stores data locally.
Cloud and edge computing offer distinct advantages based on latency, data sensitivity, and network availability; a hybrid approach often maximizes benefits.