You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Best-Effort Simulation-Based Timing Analysis using Hill-Climbing with Random Restarts

Fulltext:


Publication Type:

Report - MRTC

ISRN:

MDH-MRTC-236/2009-1-SE


Abstract

Today, many companies developing real-time systems have no means for accurate timing analysis, as the soft- ware violates the assumptions of traditional analytical methods for response-time analysis, and are too complex for exhaustive analysis using e.g. model checking. This paper presents an efficient best-effort approach for timing analysis targeting such systems, where simulations of a detailed system model are controlled by a simple yet novel optimization algorithm, based on hill climbing with ran- dom restarts (HCRR). Using a simulation-based approach implies that the result is not guaranteed to be the worst- case response time, but on the other hand, the method can handle in principle any software design. Unlike previous approaches, the new algorithm directly manipulates sim- ulation parameters such as execution times, arrival jitter and input stimulus. A thorough evaluation is also presented, where HCRR is compared to Monte Carlo simulation (the current state- of-practice) and a previously proposed method. The eval- uation is performed using a set of simulation models con- structed from existing systems in the robotics and vehicular domain, and shows that for the three models investigated, the proposed method was 4-11% more accurate and vastly more efficient than the other methods. In our evaluation, HCRR found the second-best result on average 42 times faster than the second-best method. For the largest model, HCRR used only 7.6 % of the simulations needed by the second-best method to reach the same result, implying that HCRR scales to larger systems. For the most realistic model, our new method found the highest-known response time 1 628 times faster than the second-best method.

Bibtex

@techreport{Bohlin1415,
author = {Markus Bohlin and Yue Lu and Johan Kraft and Thomas Nolte},
title = {Best-Effort Simulation-Based Timing Analysis using Hill-Climbing with Random Restarts},
number = {ISSN 1404-3041 ISRN MDH-MRTC-236/2009-1-SE},
month = {June},
year = {2009},
url = {http://www.es.mdu.se/publications/1415-}
}