Efficient implementation of tight response-times for tasks with offsets

Abstract

Earlier approximate response time analysis (RTA) methods for tasks with offsets (transactional task model) exhibit two major deficiencies: (i) They overestimate the calculated response times resulting in an overly pessimistic result. (ii) They suffer from time complexity problems resulting in an RTA method that may not be applicable in practice. This paper shows how these two problems can be alleviated and combined in one single fast-and-tight RTA method that combines the best of worlds, high precision response times and a fast approximate RTA method.

Simulation studies, on randomly generated task sets, show that the response time improvement is significant, typically about 15% tighter response times in 50% of the cases, resulting in about 12% higher admission probability for low priority tasks subjected to admission control. Simulation studies also show that speedups of more than two orders of magnitude, for realistically sized tasks sets, compared to earlier RTA analysis techniques, can be obtained.

Other improvements such as Palencia Gutiérrez, González Harbour (Proceedings of the 20th IEEE real-time systems symposium (RTSS), pp. 328–339, 1999), Redell (Technical Report TRITA-MMK 2003:4, Dept. of Machine Design, KTH, 2003) are orthogonal and complementary which means that our method can easily be incorporated also in those methods. Hence, we conclude that the fast-and-tight RTA method presented is the preferred analysis technique when tight response-time estimates are needed, and that we do not need to sacrifice precision for analysis speed; both are obtained with one single method.