What concept refers to processing data within the network to save energy?

The concept that refers to processing data within the network to save energy is known as In-Network Processing. This approach is crucial in scenarios where data is generated at various points in a network, such as in Internet of Things (IoT) devices. Instead of sending all raw data to a central location for processing, In-Network Processing allows data to be filtered, aggregated, and analyzed closer to its source. This minimizes the need for extensive data transmission, which can consume significant energy and bandwidth.

By keeping more processing tasks local and only transmitting the most relevant or summary data, energy consumption is reduced, ultimately leading to improved efficiency in data management and energy usage. This method aligns with the goals of efficient resource management in distributed networks and supports sustainable practices in data handling.

Edge Processing, while related to local processing, tends to focus more on processing at the edge of the network, which can happen outside the network infrastructure itself, often at the devices or gateway level. Distributed Computing involves a broader concept of distributing computation across multiple systems, and Data Optimization generally relates to techniques that improve data storage and retrieval efficiency but does not specifically address energy savings through processing within the network.