äärearvutuslikud

äärearvutuslikud refers to a Finnish term that translates to "edge computing" in English. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is done in order to improve response times and save bandwidth. Instead of sending all data to a centralized cloud for processing, edge computing processes data locally, at or near the device that generates it.

The primary motivation behind edge computing is to reduce latency. In many applications, such as autonomous vehicles, industrial automation, and real-time analytics, even small delays in data processing can have significant consequences. By processing data at the edge, the time it takes for data to travel to a central server and back is drastically reduced. This enables faster decision-making and more responsive systems.

Another key benefit is bandwidth optimization. The volume of data generated by connected devices, often referred to as the Internet of Things (IoT), is immense. Transmitting all this raw data to the cloud can be costly and strain network resources. Edge computing allows for pre-processing and filtering of data at the edge, sending only the essential or summarized information to the cloud. This conserves bandwidth and reduces data transmission costs.

Edge computing architectures typically involve devices like sensors, gateways, and small servers deployed at the "edge" of the network. These devices perform data collection, analysis, and sometimes even actuation, interacting with local systems and only communicating with the central cloud when necessary for long-term storage, further analysis, or coordinated actions across multiple edge locations.