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[26 May 2014] A bachelor student at RTSLAB was awarded the best thesis award from IDA - Simon Andersson. more ...

[31 May 2012] A masters student at RTSLAB was awarded the best thesis award from IDA - Ulf Magnusson. more ...

[27 February 2008] A masters student at RTSLAB was awarded the best thesis award from IDA - Johan Sigholm. more ...

[03 March 2004] A masters student at RTSLAB was awarded the best thesis award from IDA - Tobias Chyssler. more ...

[01 Jul 2003] For second year in a row a masters student at RTSLAB was awarded the best thesis award from SNART - Mehdi Amirijoo. more ...

Master Thesis - Past Projects - Abstract

Measuring and Analysing Execution Time

ID: LIU-IDA/LITH-EX-A--09/050--SE

Autoliv has developed the Night Vision system, which is a safety system for use in cars to improve the driverís situational awareness during night conditions. It is a real-time system that is able to detect pedestrians in the traffic environment and issue warnings when there is a risk of collision. The timing behaviour of programs running on real-time systems is vital information when developing and optimising both hardware and software. As a part of further developing their Night Vision system, Autoliv wanted to examine detailed timing behaviour of a specific part of the Night Vision algorithm, namely the Tracking module, which tracks detected pedestrians. Parallel to this, they also wanted a reliable method to obtain timing data that would work for other parts of that system as well, or even other applications. A preliminary study was conducted in order to determine the most suitable method of obtaining the timing data desired. This resulted in a measurement-based approach using software profiling, in which the Tracking module was measured using various input data. The measurements were performed on simulated hardware using both a cycle accurate simulator and measurement tools from the system CPU manufacturer, as well as tools implemented specifically to handle input and output data. The measurements resulted in large amounts of data used to compile performance statistics. Using different scenarios in the input data, we were able to obtain timing characteristics for several typical situations the system may encounter during operation. By manipulating the input data we were also able to observe general behaviour and achieve artificially high execution times, which serves as indications on how the system responds to irregular and unexpected input data. The method used for collecting timing information was well suited for this particular project. It provided the possibility to analyse behavior in a better way than other, more theoretical, approaches would have. The method is also easily adaptable to other parts of the Night Vision system, or other systems, with only minor adjustments to measurement environment and tools.

Keywords: WCET, Dynamic timing analysis, CPU load

File: Click here to download/view the thesis

Author(s): Henrik Liljeroth

Contact: Simin Nadjm-Tehrani

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