Measurement-based probabilistic timing analysis: Lessons from an integrated-modular avionics case study

Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular can mitigate some of the problems that impair current worst-case execution time (WCET) analysis techniques. MBPTA computes tight WCET bounds expressed as probabilistic exceedance functions, without needing much information on the hardware and software internals of the system. Classic WCET analysis has information needs that may be costly and difficult to satisfy, and their omission increases pessimism. Previous work has shown that MBPTA does well with benchmark programs. Real-world applications however place more demanding requirements on timing analysis than simple benchmarks. It is interesting to see how PTA responds to them. This paper discusses the application of MBPTA to a real avionics system and presents lessons learned in that process.

[1]  Francisco J. Cazorla,et al.  Probabilistic timing analysis on conventional cache designs , 2013, 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[2]  George Lima,et al.  An Approach for Estimating Execution Time Probability Distributions of Component-based Real-Time Systems , 2009, J. Univers. Comput. Sci..

[3]  Tullio Vardanega,et al.  A Time-composable Operating System , 2012, WCET.

[4]  Gerard J. M. Smit,et al.  A mathematical approach towards hardware design , 2010, Dynamically Reconfigurable Architectures.

[5]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[6]  Tullio Vardanega,et al.  ON THE INDUSTRIAL FITNESS OF WCET ANALYSIS , 2011 .

[7]  Raimund Kirner,et al.  Principles of timing anomalies in superscalar processors , 2005, Fifth International Conference on Quality Software (QSIC'05).

[8]  Lucia Lo Bello,et al.  Towards stochastic response-time of hierarchically scheduled real-time tasks , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[9]  John P. Lehoczky,et al.  Real-time queueing theory , 1996, 17th IEEE Real-Time Systems Symposium.

[10]  Pierre-Emmanuel Hladik,et al.  Efficient Stochastic Analysis of Real-Time Systems via Random Sampling , 2010, 2010 22nd Euromicro Conference on Real-Time Systems.

[11]  Luigi Palopoli,et al.  Efficient and robust probabilistic guarantees for real-time tasks , 2012, J. Syst. Softw..

[12]  Alan Burns,et al.  Statistical analysis of WCET for scheduling , 2001, Proceedings 22nd IEEE Real-Time Systems Symposium (RTSS 2001) (Cat. No.01PR1420).

[13]  Raimund Kirner,et al.  Obstacles in Worst-Case Execution Time Analysis , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[14]  최진영,et al.  SCADE를 이용한 리눅스 디바이스 드라이버 개발 , 2007 .

[15]  Gabriel A. Moreno,et al.  Statistical-Based WCET Estimation and Validation , 2009, WCET.

[16]  Luca Benini,et al.  Robust Scheduling of Task Graphs under Execution Time Uncertainty , 2013, IEEE Transactions on Computers.

[17]  J. V. Bradley Distribution-Free Statistical Tests , 1968 .

[18]  Sasikumar Punnekkat,et al.  Probabilistic preemption control using frequency scaling for sporadic real-time tasks , 2012, 7th IEEE International Symposium on Industrial Embedded Systems (SIES'12).

[19]  Stéphane Girard,et al.  A Goodness-of-fit Test for the Distribution Tail , 2007 .

[20]  Jason A. Poovey Characterization of the EEMBC Benchmark Suite , 2007 .

[21]  Thomas M. Conte,et al.  A Benchmark Characterization of the EEMBC Benchmark Suite , 2009, IEEE Micro.

[22]  Liliana Cucu-Grosjean,et al.  Re-sampling for statistical timing analysis of real-time systems , 2012, RTNS '12.

[23]  Jan Gustafsson,et al.  The Mälardalen WCET Benchmarks: Past, Present And Future , 2010, WCET.

[24]  Liliana Cucu-Grosjean,et al.  A component-based framework for modeling and analyzing probabilistic real-time systems , 2011, ETFA2011.

[25]  Liliana Cucu-Grosjean,et al.  Measurement-Based Probabilistic Timing Analysis for Multi-path Programs , 2012, 2012 24th Euromicro Conference on Real-Time Systems.

[26]  Liliana Cucu-Grosjean,et al.  A new way about using statistical analysis of worst-case execution times , 2011, SIGBED.

[27]  Liliana Cucu-Grosjean,et al.  PROARTIS: Probabilistically Analyzable Real-Time Systems , 2013, TECS.

[28]  Eduardo Tovar,et al.  A framework for the response time analysis of fixed-priority tasks with stochastic inter-arrival times , 2006, SIGBED.

[29]  Nathan Fisher,et al.  Efficient Admission Control for Enforcing Arbitrary Real-Time Demand-Curve Interfaces , 2012, 2012 IEEE 33rd Real-Time Systems Symposium.

[30]  Liliana Cucu-Grosjean,et al.  PROARTIS: Probabilistically Analysable Real-Time Systems , 2012 .

[31]  S. Nadarajah,et al.  Extreme Value Distributions: Theory and Applications , 2000 .

[32]  Chang-Gun Lee,et al.  Stochastic analysis of periodic real-time systems , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

[33]  Alberto L. Sangiovanni-Vincentelli,et al.  Using Statistical Methods to Compute the Probability Distribution of Message Response Time in Controller Area Network , 2010, IEEE Transactions on Industrial Informatics.

[34]  Rolf Ernst,et al.  Monitoring Arbitrary Activation Patterns in Real-Time Systems , 2012, 2012 IEEE 33rd Real-Time Systems Symposium.