Analyzing Stochastic Fixed-Priority Real-Time Systems

Traditionally, real-time systems require that the deadlines of all jobs be met. For many applications, however, this is an overly stringent requirement. An occasional missed deadline may cause decreased performance but is nevertheless acceptable. We present an analysis technique by which a lower bound on the percentage of deadlines that a periodic task meets is determined and compare the lower bound with simulation results for an example system. We have implemented the technique in the PERTS real-time system prototyping environment [6, 7].

[1]  Jun Sun,et al.  Perts: a Prototyping Environment for Real-Time Systems , 1996, Int. J. Softw. Eng. Knowl. Eng..

[2]  Azer Bestavros,et al.  The Statistical Rate Monotonic Scheduling Workbench , 1998 .

[3]  R. K. Shyamasundar,et al.  Introduction to algorithms , 1996 .

[4]  H. Nussbaumer Fast Fourier transform and convolution algorithms , 1981 .

[5]  H. Nussbaumer The Fast Fourier Transform , 1982 .

[6]  John P. Lehoczky,et al.  The rate monotonic scheduling algorithm: exact characterization and average case behavior , 1989, [1989] Proceedings. Real-Time Systems Symposium.

[7]  Azer Bestavros,et al.  Statistical rate monotonic scheduling , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[8]  Chung Laung Liu,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[9]  John P. Lehoczky,et al.  Fixed priority scheduling of periodic task sets with arbitrary deadlines , 1990, [1990] Proceedings 11th Real-Time Systems Symposium.

[10]  Jun Sun,et al.  Probabilistic performance guarantee for real-time tasks with varying computation times , 1995, Proceedings Real-Time Technology and Applications Symposium.