Response time analysis is required both for on-line admission of applications in dynamic systems and as an integral part of design tools for complex distributed real-time systems. We consider sporadic tasks with fixed-priorities and arbitrary deadlines to be executed upon a uniprocessor platform. Pseudo-polynomial time algorithms are known for computing exact worst-case response times for this task model. Nevertheless, the problem is known NP-hard and there cannot exist a constant approximation algorithm for response time computation, unless P=NP. We propose a fully polynomial time approximation scheme (FPTAS) for computing response time upper bounds under resource augmentation. The resource augmentation is defined as the processor speedup factor bounded by (1 + 1/k), where kdef[1 = ε]-1 for any constant ε ∈ (0;1), the FPTAS accuracy parameter. This algorithm is best possible in the sense that resource augmentation is indeed necessary for an efficient response time calculation.

In this paper we propose parametric approximation algorithm (Fully Polynomial Time Approximation Scheme - FPTAS) that defines a compromise on the precision of computed worst-case response time upper bounds and the amount of extra processor speed required to achieve exact worst-case response times. Such a result fills the remaining gap between our previously published work [11] and also extends them to tasks with arbitrary relative deadlines. The method has been implemented and numerical results monitoring speedup factors are presented.

Since worst case response times must be determined repeatedly during the interactive design of real-time application systems, repeated exact computation of such response times would slow down the design process considerably. In this research, we identify three desirable properties of estimates of the exact response times: continuity with respect to system parameters, efficient computability, and approximability. We derive a technique possessing these properties for estimating the worst-case response time of sporadic task systems that are scheduled using fixed priorities upon a preemptive uniprocessor.

Feasibility analysis algorithms are based on particular metrics such as processor utilization, load factor, processor demand, response-times, etc. The design of efficient algorithms for computing these metrics is a major issue in real-time scheduling theory. In this paper we propose two FPTASs (fully-polynomial time approximation schemes) for checking feasibility of static-priority tasks subjected to release jitters executed upon a uniprocessor platform. We then use these FPTASs for computing two upper bounds of worst-case response-times. Lastly, we show that these bounds do not achieve constant error bounds in comparison with values computed by an exact worst-case response-time analysis (performed in pseudo-polynomial time), and we present numerical experiments.