Improving Measurement-Based Timing Analysis through Randomisation and Probabilistic Analysis

The use of increasingly complex hardware and software platforms in response to the ever rising performance demands of modern real-time systems complicates the verification and validation of their timing behaviour, which form a time-and-effort-intensive step of system qualification or certification. In this paper we relate the current state of practice in measurement-based timing analysis, the predominant choice for industrial developers, to the proceedings of the PROXIMA project in that very field. We recall the difficulties that the shift towards more complex computing platforms causes in that regard. Then we discuss the probabilistic approach proposed by PROXIMA to overcome some of those limitations. We present the main principles behind the PROXIMA approach as well as the changes it requires at hardware or software level underneath the application. We also present the current status of the project against its overall goals, and highlight some of the principal confidence-building results achieved so far

Industrial experiences with resource management under software randomization in ARINC653 avionics environments

Injecting randomization in different layers of the computing platform has been shown beneficial for security, resilience to software bugs and timing analysis. In this paper, with focus on the latter, we show our experience regarding memory and timing resource management when software randomization techniques are applied to one of the most stringent industrial environments, ARINC653-based avionics. We describe the challenges in this task, we propose a set of solutions and present the results obtained for two commercial avionics applications, executed on COTS hardware and RTOS.The work leading to these results has been funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) un- der the PROXIMA Project (grant agreement 611085). Moreover, it has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence.Peer Reviewe

PROXIMA: A Probabilistic Approach to the Timing Behaviour of Mixed-Criticality Systems

International audienc

PROXIMA: Improving Measurement-Based Timing Analysis through Randomisation and Probabilistic Analysis

The use of increasingly complex hardware and software platforms in response to the ever rising performance demands of modern real-time systems complicates the verification and validation of their timing behaviour, which form a time-and-effort-intensive step of system qualification or certification. In this paper we relate the current state of practice in measurement-based timing analysis, the predominant choice for industrial developers, to the proceedings of the PROXIMA (Probabilistic real-time control of mixed-criticality multicore systems) project in that very field. We recall the difficulties that the shift towards more complex computing platforms causes in that regard. Then we discuss the probabilistic approach proposed by PROXIMA to overcome some of those limitations. We present the main principles behind the PROXIMA approach as well as the changes it requires at hardware or software level underneath the application. We also present the current status of the project against its overall goals, and highlight some of the principal confidence-building results achieved so far.The research leading to these results has received funding from the European Community’s Seventh Framework Programme [FP7/2007-2013] under the PROXIMA Project (grant agreement 611085). Carles Hern´andez is jointly funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer Reviewe