4 research outputs found
A framework for the response time analysis of fixed-priority tasks with stochastic inter-arrival times
Real-time scheduling usually considers worst-case values for the
parameters of task (or message stream) sets, in order to provide
safe schedulability tests for hard real-time systems. However,
worst-case conditions introduce a level of pessimism that is often
inadequate for a certain class of (soft) real-time systems. In this
paper we provide an approach for computing the stochastic
response time of tasks where tasks have inter-arrival times
described by discrete probabilistic distribution functions, instead
of minimum inter-arrival (MIT) values
An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems
We show a methodology for the computation of the probability of deadline miss
for a periodic real-time task scheduled by a resource reservation algorithm. We
propose a modelling technique for the system that reduces the computation of
such a probability to that of the steady state probability of an infinite state
Discrete Time Markov Chain with a periodic structure. This structure is
exploited to develop an efficient numeric solution where different
accuracy/computation time trade-offs can be obtained by operating on the
granularity of the model. More importantly we offer a closed form conservative
bound for the probability of a deadline miss. Our experiments reveal that the
bound remains reasonably close to the experimental probability in one real-time
application of practical interest. When this bound is used for the optimisation
of the overall Quality of Service for a set of tasks sharing the CPU, it
produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27,
Issue: 3, March 201