A Statistical Response-Time Analysis of Real-Time Embedded Systems

Lu, Yue; Nolte, Thomas; Bate, Iain; Cucu-Grosjean, Liliana

doi:10.1109/rtss.2012.85

Cited by 48 publications

(42 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lu [33] has addressed limitations of EVTbased analysis based on a systematic analysis framework. Further, the analysis method generally can be applied on different systems, since the target system is considered as a black box without requiring estimates of parameters such as WCETs of tasks.…”

Section: Statistical Timing Analysismentioning

confidence: 99%

“…fitting a Weibull (W) distribution; 2. fitting a Gumbel (G) distribution; 3. fitting a Normal (N) distribution; and 4. applying the Block-Maxima (BM) method presented in [33] The first three of these analyses are achieved using a standard function in R, samlmu (part of the lmom package) [27], which was chosen as other fitting functions, e.g. fitdistr, were found not to be robust (i.e.…”

Section: Statistical Analysis Toolmentioning

confidence: 99%

“…The advantage of samlmu is that it did not require initial parameters. The Block-Maxima analysis can be summarized by the following steps with full details being available in [33]. All the values chosen in the algorithm are based on standard statistical test tables [20] that have subsequently been validated through trials.…”

Section: Statistical Analysis Toolmentioning

confidence: 99%

“…precedence constraints between tasks. Implicit dependencies are those that come from the tasks sharing dependencies such as caches and execution dependencies [33]. Explicit dependencies can easily be built into task set simulators.…”

Section: Unrealistic Overheads -In a Similar Fashion To Unrealisticmentioning

confidence: 99%

“…RTNS '15 November 4-6, 2015, Lille, France Copyright 20XX ACM X-XXXXX-XX-X/XX/XX ...$15.00. [33] and messages [37].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Study of the reliability of statistical timing analysis for real-time systems

Maxim¹,

Soboczenski

Bate

et al. 2015

Proceedings of the 23rd International Conference on Real Time and Networks Systems

Self Cite

View full text Add to dashboard Cite

Probabilistic and statistical temporal analyses have been developedas a means of determining the worst-case execution and responsetimes of real-time software for decades. A number of such methodshave been proposed in the literature, of which the majority claim tobe able to provide worst-case timing scenarios with respect to agiven likelihood of a certain value being exceeded. Further, suchclaims are based on either some estimates associated with a probability,or probability distributions with a certain level of confidence.However, the validity of the claims are very much dependent on anumber of factors, such as the achieved samples and the adopteddistributions for analysis.In this paper, we investigate whether the claims made are in facttrue as well as the establishing an understanding of the factors thataffect the validity of these claims. The results are of importancefor two reasons: to allow researchers to examine whether there areimportant issues that mean their techniques need to be refined; andso that practitioners, including industrialists who are currently usingcommercial timing analysis tools based on these types of techniques,understand how the techniques should be used to ensure theresults are fit for their purposes. Study of the Reliability of Statistical Timing Analysis forReal-Time Systems ABSTRACTProbabilistic and statistical temporal analyses have been developed as a means of determining the worst-case execution and response times of real-time software for decades. A number of such methods have been proposed in the literature, of which the majority claim to be able to provide worst-case timing scenarios with respect to a given likelihood of a certain value being exceeded. Further, such claims are based on either some estimates associated with a probability, or probability distributions with a certain level of confidence. However, the validity of the claims are very much dependent on a number of factors, such as the achieved samples and the adopted distributions for analysis. This paper is the first one that puts side by side existing state of the art statistical and probabilistic analysis techniques, using the probabilistic analysis as the ground truth in order to asses the applicability and performance of the statistical technique. The evaluation clearly shows that for the experiments performed the approach can identify clear differences between a range of techniques and that these differences can be considered valid based on the trends expected from the academic theory.

show abstract

Section: Statistical Timing Analysismentioning

confidence: 99%

Section: Statistical Analysis Toolmentioning

confidence: 99%

Section: Statistical Analysis Toolmentioning

confidence: 99%

Section: Unrealistic Overheads -In a Similar Fashion To Unrealisticmentioning

confidence: 99%

“…RTNS '15 November 4-6, 2015, Lille, France Copyright 20XX ACM X-XXXXX-XX-X/XX/XX ...$15.00. [33] and messages [37].…”

Section: Introductionmentioning

confidence: 99%