Edge Computing: the solution to latency and security challenges in the IoT era
In the era of Internet of Things (IoT) demand for real-time data processing is constantly growing. There are more and more Network-connected devices that generate and transmit data in real time and traditional cloud infrastructure is not always able to meet the latency and bandwidth needs required to process this enormous amount of information.
This is where the Edge Computing a emerging technology which is transforming the way data processing is carried out instantly. In this article, we will explain what Edge Computing consists of and show some practical examples of how this technology is being used in various sectors.
What is Edge Computing?
It is a technology that consists of carrying the processing and storing data closer to the end user. Instead of sending all data to a remote cloud, edge computing uses local devices and close to the user to process and store data. That is, it is based on a distributed network of data processing devices, called edge nodes or Edge Nodes. These nodes can be IoT devices, Edge servers or any other data processing device capable of processing information in real time allowing to reduce latency and improving the user experience.
How does Edge Computing work?
Edge computing works through use of small and efficient devices, such as IoT sensors, mobile phones, routers, gateways and servers, which are placed close to end users. These devices are capable of processing and storing data locally, reducing the need to send large amounts of data over a network.
Advantages of Edge Computing
Edge computing offers a number of advantages over traditional cloud infrastructure, including:
✓ Reduced latency
By treating data at the edge of the network, that is, data processing is performed on devices or systems that are close to users rather than on remote servers in the cloud, latency is significantly reduced, allowing a faster and more efficient response to critical situations.
✓ Reduced bandwidth
Processing data at the edge of the network (closer to where the data is created) also reduces the bandwidth required for processing, resulting in significant savings on network costs.
✓ Greater security
Increases data privacy and security, as Data is processed on the local device or system before being sent to the cloud reducing the risk of data being intercepted or compromised during transmission.
Examples of application of Edge Computing
Edge computing is used in real-time applications, such as augmented reality the autonomous vehicles and the IoT devices where latency is critical.
Below are some examples of the practical applications of Edge Computing that are currently transforming various sectors.
- Precision farming: Edge computing is used in precision agriculture to collect and process data from sensors and drones in real time. This data is used to Optimize crop yields, improve resource efficiency and reduce costs. Sensors are placed close to crops and data is processed locally to ensure rapid response.
- autonomous vehicles: Also used in autonomous vehicles to process sensor data in real time. Sensors are used to collect information about the vehicle’s surroundings, such as position, speed, and distance. This data is processed locally in the vehicle to Ensure quick response and improve vehicle safety.
- Remote healthcare: allows improving the quality of patient care. Monitoring devices are placed near the patient to collect information about your health in real time such as biometric data, heart rate and blood pressure. This data is processed locally and sent to healthcare professionals so they can make quick and accurate decisions.
- Cloud gaming– Reduces latency and improves user experience. Game servers are located close to players to process data locally and reduce the amount of data sent over the network. This ensures a faster and smoother gaming experience.
- Smart cities– Used in smart building control to process and store data locally. Sensors, cameras, and IoT devices collect information about the building, such as temperature, humidity, and lighting. This data is processed locally to control heating, ventilation and air conditioning systems, which improves energy efficiency and enables smarter resource management.
- Digital Banking: In digital banking, the implementation of Edge Computing allows the instant analysis of large volumes of financial data and the detection of fraud in financial transactions in real time, which is why its use improves the security, speed and efficiency of financial operations.