What is Edge computing?

It is a part of distributed topology which focuses on reducing the latency and bandwidth use by bringing computation and data storage closer to devices rather than relying on central locations which can be many miles away. In less difficult terms, it implies running fewer processes in the cloud and moving those processes to local places, for example, on a client’s PC, an IoT gadget, or an edge server. This is done with the goal that information, particularly real-time information, doesn’t suffer latency that can influence an application’s exhibition. But it as of now is just a philosophy, there is no actual analytical framework to prove it.

Reason or need to use this technology?

At some point we all are facing problems due to latency. You may not be critical, but a large organization that needs on-time results can lead to huge losses due to latency. For example you are playing an FPS game and you are a good player. You are playing a game and suddenly high latency kicks in. Now what happens next is, your headshot can pretty much become a miss shot. Now this is just a game, imagine an organization performing a very important computation that needs constant data feeding to complete the complex calculations. A small delay in the process can lead to error, wrong results or even data loss.

Cloud computing vs edge computing what’s the difference?

Note: Edge computing and cloud computing are miles apart in their functionality and cannot replace one another. Edge computing is used to process time-sensitive data, while cloud computing is used to process data that is not time-driven.

  • Edge Computing is used for the real-time monitoring and analysis, whereas Cloud Computing is essentially used for the back-end data access.
  • Cloud computing is preferred over edge computing in terms of power processing.
  • Edge computing can be a preferred choice over cloud computing because it ensures lower management costs.
  • The technology can reduce the latency of information processing because it relocates crucial data processing to the edge of the network.
  • Edge computing distributes data processes across different locations which makes data deliverable to nearest locations and processing at the edge.

Conclusion

It was invented to reduce the latency and bandwidth cost for IoT devices over long distances. But the growth of real-time application itself depicts the future scope of this technology as it is time-driven.

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