The Deferrable Server Algorithm for Enhanced Aperiodic Responsiveness in Hard Real-Time Environments
IEEE Transactions on Computers
An Optimal Algorithm for Scheduling Soft Aperiodic Tasks in Dynamic-Priority Preemptive Systems
IEEE Transactions on Software Engineering
Minimizing Aperiodic Response Times in a Firm Real-Time Environment
IEEE Transactions on Software Engineering
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Optimal Deadline Assignment for Scheduling Soft Aperiodic Tasks in Hard Real-Time Environments
IEEE Transactions on Computers
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Integrating Multimedia Applications in Hard Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
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In a real-time system with both hard real-time periodic jobs and soft real-time aperiodic jobs, it is important to guarantee that the deadline of each periodic job is met, as well as to provide a fast response time for each aperiodic job. We propose an algorithm, called Proportional Slack Reserve (PSR), that produces an efficient schedule for such an environment. For every execution unit of a periodic job, the PSR algorithm reserves time which can be used for execution of aperiodic jobs. If reserved time is not available, the algorithm assigns a deadline to an aperiodic job for achieving better responsiveness of aperiodic jobs. The proposed algorithm can fully utilize processing power while meeting all deadlines of periodic jobs. It can also easily reclaim the time unused by the periodic job. We analytically show that for each aperiodic job, the response time in a PSR schedule is no longer than that in a TBS schedule, which is known to be efficient for servicing aperiodic jobs. We also present simulation results in which the response time of PSR is significantly improved over that of TBS, and moreover the performance of PSR compares favorably with TB(N) considering scheduling overhead.