What is edge computing

What is Edge Computing?

Edge computing brings data processing and storage closer to the devices or systems that generate the data. Instead of relying on centralized cloud servers, you process data locally at the “edge” of the network, near IoT devices, sensors, or local servers.

It reduces the time it takes for data to travel, enabling faster, real-time responses and minimizing latency.

Why is Edge Computing Important?

Edge computing plays a crucial role in today’s data-driven world, especially with the growing number of connected devices and IoT systems. It allows for real-time data processing, which is essential for applications that need immediate responses, such as autonomous vehicles, smart manufacturing, healthcare monitoring, and augmented reality.

By processing data locally, you reduce the amount of data sent over the internet to cloud servers, optimizing bandwidth usage and cutting costs. It also enhances security and privacy because you can process and store sensitive data closer to its source, minimizing the risk of exposure to external threats.

How Does Edge Computing Work?

In a typical cloud computing setup, data is sent from devices to centralized cloud servers for processing. It may cause delays since the data travels long distances, creating latency issues. Edge computing solves this by moving the processing power closer to the data source.

One can deploy edge devices—such as IoT gateways, routers, or local servers—near the data source, allowing them to handle processing, analysis, and storage.

After processing, the cloud receives only the relevant data for further analysis or storage. This method reduces the amount of raw data that travels across networks, allowing for quicker decision-making and more efficient resource use.

Difference Between Edge Computing & Cloud Computing?

The primary difference between edge computing and cloud computing is where the data processing happens. In cloud computing, centralized cloud data centres process the data generated by devices located far from those devices. This can lead to higher latency and slower response times.

With edge computing, data is processed locally, close to its source. It reduces the need for data to travel long distances, resulting in faster processing times and lower latency.

Cloud computing works best for large-scale data storage and complex computing tasks, while edge computing excels in situations requiring real-time responses and lower bandwidth consumption.