Monte Carlo Response-Time Analysis

Bozhko, Sergey; Brüggen, Georg von der; Brandenburg, Björn B.

doi:10.1109/rtss52674.2021.00039

Cited by 19 publications

(6 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is a natural step in our opinion for the use of the analysis provided in this work. For example, the analysis we have presented in this paper is well suited for an application of a Monte-Carlo response time analysis [3] which has recently been proven efficient.…”

Section: Discussionmentioning

confidence: 99%

Response Time Stochastic Analysis for Fixed-Priority Stable Real-Time Systems

Zagalo

Abdeddaïm

Bar-Hen

et al. 2023

IEEE Trans. Comput.

View full text Add to dashboard Cite

In this paper, we prove that a mean system utilization smaller than one is a necessary condition for the feasibility of real-time systems. Such systems are defined as stable. Stable systems have two distinct states: a transient state, followed by a steady-state where the same distribution of response times is repeated infinitely for each task. We prove that the Liu and Layland theorem holds for stable probabilistic real-time systems with implicit deadlines, we provide an analytical approximation of response times for each of those two states and a bound of the instant when a real-time system becomes steady.

show abstract

Section: Discussionmentioning

confidence: 99%

Response Time Stochastic Analysis for Fixed-Priority Stable Real-Time Systems

Zagalo

Abdeddaïm

Bar-Hen

et al. 2023

IEEE Trans. Comput.

View full text Add to dashboard Cite

show abstract

“…The reason is that the time and space complexity is exponential in the number of jobs released in the considered interval, which can easily be hundreds or thousands of jobs for practical systems. Hence, several distinct approaches have been proposed to mitigate or even avoid the issues (by trading faster calculation for pessimism), e.g., down-sampling approaches [24], [25], [27], [30], concentration inequalities [8], [9], [35], task-level convolution [35], and the Monte Carlo response time analysis [6].…”

Section: B Techniques For Efficient Calculationmentioning

confidence: 99%

“…When calculating the probabilistic response time of a specific job using convolution with down-sampling [25], [27], [30] or the Monte Carlo response time analysis [6] the unsound critical instant is merely adopted as a specific evaluation scenario. Although the considered scenario is not the worst-case scenario, the technical contribution hence remains unaffected.…”

Section: B Techniques For Efficient Calculationmentioning

confidence: 99%

“…The efficient calculation techniques discussed in this subsection can still directly be applied to upper-bound the probabilistic response time distribution (for [6], [25], [30]) or the WCRTEP (for [8], [9], [35]) by replacing the adoption of the unsound critical instant theorem in these results with the sound analyses in Theorem 11 or Theorem 14 provided in this work.…”

Section: B Techniques For Efficient Calculationmentioning

confidence: 99%

“…Since then, the critical instant theorem under the probabilistic setup by Maxim and Cucu-Grosjean [25] has been widely used in the literature [26], [31], [32]. Due to an essential complication in probabilistic response-time analysis (i.e., convolution over multiple random variables), several techniques have been developed to tackle issues of intractability through various means, e.g., down-sampling [24], [25], [27], [30], concentration inequalities [8], [9], [35], task-level convolution [35], and Monte-Carlo simulation [6]. Our Contributions: This paper revisits the critical instant for the probabilistic timing analysis of sporadic real-time task sets, formally defined as the worst-case response time exceedance probability (WCRTEP) in Definition 2 and the worst-case deadline failure probability (WCDFP) in Definition 4.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Critical Instant for Probabilistic Timing Guarantees: Refuted and Revisited

Chen

Günzel

Brüggen

et al. 2022

2022 IEEE Real-Time Systems Symposium (RTSS)

Self Cite

View full text Add to dashboard Cite

A formal framework to design and prove trustworthy memory controllers

Lisboa Malaquias,

Asavoae,

Brandner

2023

Real-Time Syst

View full text Add to dashboard Cite

In order to prove conformance to memory standards and bound memory access latency, recently proposed real-time DRAM controllers rely on paper and pencil proofs, which can be troubling: they are difficult to read and review, they are often shown only partially and/or rely on abstractions for the sake of conciseness, and they can easily diverge from the controller implementation, as no formal link is established between both. We propose a new framework written in Coq, in which we model a DRAM controller and its expected behaviour as a formal specification. The trustworthiness in our solution is two-fold: (1) proofs that are typically done on paper and pencil are now done in Coq and thus certified by its kernel, and (2) the reviewer’s job develops into making sure that the formal specification matches the standards—instead of performing a thorough check of the mathematical formalism. Our framework provides a generic DRAM model capturing a set of controller properties as proof obligations, which all implementations must comply with. We focus on properties related to the assertiveness that timing constraints are respected, every incoming request is handled in bounded time, and the DRAM command protocol is respected. We refine our specification with two implementations based on widely-known arbitration policies—First-in First-Out (FIFO) and Time-Division Multiplexing (TDM). We extract proved code from our model and use it as a “trusted core” on a cycle-accurate DRAM simulator.

show abstract

Monte Carlo Response-Time Analysis

Cited by 19 publications

References 46 publications

Response Time Stochastic Analysis for Fixed-Priority Stable Real-Time Systems

Response Time Stochastic Analysis for Fixed-Priority Stable Real-Time Systems

Critical Instant for Probabilistic Timing Guarantees: Refuted and Revisited

A formal framework to design and prove trustworthy memory controllers

Contact Info

Product

Resources

About