PROARTIS: Probabilistically Analyzable Real-Time Systems

Static timing analysis is the state-of-the-art practice of ascertaining the timing behavior of current-generation real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of static timing analysis. In particular, the effort of acquiring (1) detailed information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behavior of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the timing analysis walls. In this vision-statement article, we present probabilistic timing analysis, a novel approach to the analysis of the timing behavior of next-generation real-time embedded systems. We show how probabilistic timing analysis attacks the timing analysis walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how probabilistic timing analysis reduces the extent of knowledge about the execution platform required to produce probabilistically accurate WCET estimations.

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

[2]  A. Raghunathan,et al.  LOTTERYBUS: a new high-performance communication architecture for system-on-chip designs , 2001, Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232).

[3]  Jakob Engblom,et al.  The worst-case execution-time problem—overview of methods and survey of tools , 2008, TECS.

[4]  Guillem Bernat,et al.  WCET analysis of probabilistic hard real-time systems , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

[5]  Bernd Becker,et al.  A Definition and Classification of Timing Anomalies , 2006, WCET.

[6]  Alan Burns,et al.  Probabilistic timing analysis: An approach using copulas , 2005, J. Embed. Comput..

[7]  Alan Burns,et al.  Realism in Statistical Analysis of Worst Case Execution Times , 2010, WCET.

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

[9]  Jun Sun,et al.  Probabilistic performance guarantee for real-time tasks with varying computation times , 1995, Proceedings Real-Time Technology and Applications Symposium.

[10]  Jane W.-S. Liu,et al.  Analyzing Stochastic Fixed-Priority Real-Time Systems , 1999, TACAS.

[11]  Emery D. Berger,et al.  DieHard: probabilistic memory safety for unsafe languages , 2006, PLDI '06.

[12]  J. T. Lewis,et al.  AN INTRODUCTION TO LARGE DEVIATIONS FOR TELETRAF C ENGI-NEERS , 1996 .

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

[14]  Shuchang Zhou,et al.  An Efficient Simulation Algorithm for Cache of Random Replacement Policy , 2010, NPC.

[15]  Albrecht Kadlec,et al.  Avoiding Timing Anomalies Using Code Transformations , 2010, 2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing.

[16]  Joaquín Entrialgo,et al.  Stochastic analysis of real-time systems under preemptive priority-driven scheduling , 2008, Real-Time Systems.

[17]  Francisco J. Cazorla,et al.  Using Randomized Caches in Probabilistic Real-Time Systems , 2009, 2009 21st Euromicro Conference on Real-Time Systems.

[18]  Per Stenström,et al.  Timing anomalies in dynamically scheduled microprocessors , 1999, Proceedings 20th IEEE Real-Time Systems Symposium (Cat. No.99CB37054).

[19]  Nicolas Navet,et al.  Probabilistic Estimation of Response Times Through Large Deviations , 2007, RTSS 2007.

[20]  R. Rajkumar,et al.  Optimal partitioning for quantized EDF scheduling , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

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

[22]  Giorgio C. Buttazzo,et al.  Integrating multimedia applications in hard real-time systems , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

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

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

[25]  B. Gnedenko Sur La Distribution Limite Du Terme Maximum D'Une Serie Aleatoire , 1943 .