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In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.
In preemptible scheduling, dynamic priority scheduling such as earliest deadline first (EDF) provides the optimal schedulable utilization of 1 in contrast to less than 0.69 with fixed priority scheduling such as rate-monotonic (RM). [1] In periodic real-time task model, a task's processor utilization is defined as execution time over period.
Therefore, another system is needed. Real-time databases may be modified to improve accuracy and efficiency and to avoid conflict, by providing deadlines and wait periods to insure temporal consistency. Real-time database systems offer a way of monitoring a physical system and representing it in data streams to a database. A data stream, like ...
This is a list of real-time operating systems (RTOSs). This is an operating system in which the time taken to process an input stimulus is less than the time lapsed until the next input stimulus of the same type.
The term "stream" is used in a number of similar ways: "Stream editing", as with sed, awk, and perl. Stream editing processes a file or files, in-place, without having to load the file(s) into a user interface. One example of such use is to do a search and replace on all the files in a directory, from the command line.
This approach to architecture attempts to balance latency, throughput, and fault-tolerance by using batch processing to provide comprehensive and accurate views of batch data, while simultaneously using real-time stream processing to provide views of online data. The two view outputs may be joined before presentation.
A real-time scheduling system is composed of the scheduler, clock and the processing hardware elements. In a real-time system, a process or task has schedulability; tasks are accepted by a real-time system and completed as specified by the task deadline depending on the characteristic of the scheduling algorithm. [1]
The task's priority is set to the priority ceiling of the resource, thus no task that may lock the resource is able to get scheduled. This ensures the OCPP property that "A task can only lock a resource if its dynamic priority is higher than the priority ceilings of all resources locked by other tasks". [2]