Abstract
In hard real-time task systems where periodic and aperiodic tasks coexist, the object of task scheduling is to reduce the response time of the aperiodic tasks while meeting the deadline of periodic tasks. Total bandwidth server (TBS) and advanced TBS (ATBS) are used in dynamic priority systems. However, these methods are not optimal solutions because they use the worst-case execution time (WCET) or the estimation value of the actual execution time of the aperiodic tasks. This paper presents an online slack-stealing algorithm called SSML that can make significant response time reducing by modification of look-ahead earliest deadline first (laEDF) algorithm as the slack computation method. While the conventional slack-stealing method has a disadvantage that the slack amount of each frame must be calculated in advance, SSML calculates the slack when aperiodic tasks arrive. Our simulation results show that SSML outperforms the existing TBS based algorithms when the periodic task utilization is higher than 60%. Compared to ATBS with virtual release advancing (VRA), the proposed algorithm can reduce the response time up to about 75%. The performance advantage becomes much larger as the utilization increases. Moreover, it shows a small performance variation of response time for various task environments.
Highlights
Modern complex real-time control systems should perform computationally intensive activities within a specified time duration
Total bandwidth server (TBS) based algorithms when the periodic task utilization is higher than 60%
The performance advantage becomes much larger as the utilization increases
Summary
Modern complex real-time control systems should perform computationally intensive activities within a specified time duration. Dynamic scheduling algorithms, such as the earliest deadline first (EDF), can be used to increase processor utilization [5] Dynamic priority servers such as total bandwidth server (TBS) [2] and constant bandwidth server (CBS) [6] greatly affect the responsiveness of the aperiodic tasks. The advanced TBS (ATBS) was proposed in [7,8] to reduce the aperiodic task response time, where the deadline of the currently arrived aperiodic task is predicted based on the execution time of the previously performed aperiodic tasks. We propose an online slack-stealing method by using the modification of laEDF to improve the scheduling performance of mixed tasks in real-time systems. Unlike the existing slack-stealing method, the proposed algorithm operates under dynamic priority scheduling to increase processor utilization. The performance advantage becomes much larger as the utilization increases
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