Edge computing brings computation and data storage closer to the sources of data — sensors, devices and users — instead of relying on a distant centralized cloud.
By processing data at the network edge, it reduces latency, saves bandwidth and enables real-time decision making for applications like autonomous vehicles and IoT.
In traditional cloud computing, data travels to remote data centers for processing, introducing latency. Edge computing places small processing nodes (edge servers, gateways) near the data origin so time-critical processing happens locally and only summarized data goes to the cloud.
This layered model — device, edge, cloud — balances low-latency local responses with the heavy storage and analytics power of the cloud.
| Aspect | Details |
|---|---|
| Branch | Computer Science Engineering (CSE) |
| Topic Type | Technical Seminar / Project Report |
| Difficulty | Intermediate – Advanced |
| Best For | Final-year BTech seminars & presentations |
| Includes | Explanation, key points, FAQs & references |