Читать книгу Understanding Infrastructure Edge Computing - Alex Marcham - Страница 30

Many pieces of data have a window of time in which they are most useful. If within that time period they cannot be processed and used to extract an actionable insight, the value of that data decreases exponentially. Examples of this type of data include many real‐time applications; for example, in the scenario of an industrial robotics control system, instructing the system to perform an action such as orienting a robotic arm in a certain position to catch a piece of falling material is of limited use if the command reaches the arm too late to perform that action in a safe manner before the material falls.

Data velocity is the name given to this concept. If data for real‐time applications can be processed and used to extract insight within the shortest possible span of time since its creation or collection, that data and the resulting insight are able to provide their highest possible value to their end user. This processing must occur at a point of aggregation in terms of both network topology and compute resources, such that the resulting data analysis has the full context of relevant events and the power to perform the analysis at an acceptable rate for the application and its users to prevent any issues.