The phrase "actual execution time" is correct and usable in written English.
It can be used in contexts related to computing, programming, or performance measurement to refer to the real time taken to execute a process or task.
Example: "The actual execution time of the algorithm was significantly lower than expected, leading to improved performance."
Alternatives: "real execution time" or "true execution time".
This way, we can automatically estimate the actual execution time for a process.
The former schedules the tasks to resources before the actual execution time and later schedules them at the time of execution.
If task m is stretched by a slowdown factor ν k, then its actual execution time at frequency f k is L m /ν k.
Finally, considering the fact that the actual execution time (AET) of many tasks may be less than the worst-case execution time (WCET), a global dynamic scheduling algorithm is proposed to maximize the energy efficiency while ensuring the reliability.
As showed in Figure16, by comparing the actual execution time (AET) of a task T1 with its worst-case execution time (WCET) C1, (DSF) technique determines the value of the dynamic slack.
An effective technique for meeting real-time constraints is to keep the processor utilization on each node at or below the schedulable utilization bound, even though each task's actual execution time may have large uncertainties and deviate a lot from its estimated value.
Figure 8 shows the differences between the execution times theoretically calculated in Section 6 and the actual execution times measured when executing the application.
In Figure 8, it can be seen that actual execution times are much longer than theoretical times.
Figure 8 Comparison between the theoretical and the actual execution times when using a computer with hyperthreading.
The obtained results confirm that the developed procedures have reasonable complexities and that their actual execution times are of the order of seconds.
With a polynomial-time complexity O(EVlogE) and actual execution times (in milliseconds, as observed above), we are confident that the proposed maximal matching algorithms are easily scalable for very large real-world networks of several hundreds and even thousands of nodes.
