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Edge computing


Edge computing is a distributed computer architecture in which data processing is moved to the edge of the network, close to data sources such as IoT devices or local computer systems. The aim is to minimize latency, reduce bandwidth consumption and improve the efficiency of network applications by analyzing and processing data locally before sending it to a central data center or to the cloud as needed.


The development of edge computing is closely linked to the rapid growth of the Internet of Things (IoT) and the increasing number of connected devices. The need to process large amounts of data efficiently and ensure fast response times has led to the development of edge computing solutions. These make it possible to carry out critical data analyzes directly at the point of origin of the data, instead of requiring transmission over long distances to the cloud.

Areas of application

Edge computing is widely used in industries where real-time analysis and decisions are critical, such as manufacturing, healthcare, transportation, and telecommunications. For example, manufacturing facilities can use edge computing to monitor and control machines in real time, resulting in optimized utilization and reduced operating expenses.


Edge computing offers numerous benefits, including improved responsiveness by processing data close to the source, resulting in faster decision-making processes. It also enables a significant reduction in data transfer and associated costs as well as increased security, as sensitive data can be processed and stored locally instead of being transmitted over the Internet.


The challenges of using edge computing include managing and securing many devices, as well as integration with existing cloud services and central data processing systems. It also requires continuous maintenance and updating of systems installed at the edge of the network to ensure security and efficiency.


A practical example of edge computing is managing traffic systems in a city, where traffic flow data is processed locally to adjust traffic lights and signs in real time. Another example could be a smart home security system that uses local computing to respond instantly to burglaries or other security threats without relying on a connection to the cloud.


Edge computing represents a significant innovation in network architecture that aims to bring data processing to the edge of the network. It offers significant benefits in terms of speed, efficiency, and security, but also poses new challenges in managing and securing distributed systems.