The public defense of Filip Markovic's doctoral thesis in Computer Science and Engineering
The public defense of Filip Markovic's doctoral thesis in Computer Science and Engineering will take place at Mälardalen University, room Delta and online (Zoom) at 13.30 on June 15, 2020.
Title: “Preemption-delay aware schedulability analysis of real-time systems”.
Serial number: 315.
The faculty examiner is Associate Professor Enrico Bini, University of Torino, Italy, and the examining committee consists of Professor Giuseppe Lipari, University of Lille, France; Professor Paul Pop, DTU, Denmark; and Associate Professor Javier Gutiérrez, University of Cantabria, Spain.
Reserve; Associate Professor Alessandro Papadopoulos, Mälardalen University.
In some computer systems, it is not only important to produce the correct result for each activity (e.g. computing that the radiation is 15 000 Roentgen and not only 3), but it is also important that activities are finished within a specified time, e.g. notifying the personnel in a nuclear power plant about a radiation leakage. If the leakage is not detected and the notification sent within a few seconds from the moment it happened, then the life of the personnel can be severely endangered. In such systems it is crucial to guarantee timeliness, meaning that we can guarantee that all of the activities that need to be performed within a specified time, will really be, regardless of the situation. For this purpose, we use scheduling, which is the mechanism that controls in what order different activities are carried out. Also, in order to test whether certain scheduling can guarantee that no timing constraints are violated we use schedulability analysis.
In this work, we present two main ways to improve schedulability analysis for a particulartype of systems by i) making a detailed analysis of the time wasted when activities interrupt each other; and ii) dividing activities in a clever way when more than one processor is available. Together, the proposed approaches result in more precise analysis and better use of scarce computational resources.