Lana Josipovic: Catalogue data in Autumn Semester 2024 |
| Name | Prof. Dr. Lana Josipovic |
| Field | Digital Systems and Design Automation |
| Address | Inst. f. Techn. Informatik u. K. ETH Zürich, ETZ G 82 Gloriastrasse 35 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 70 61 |
| ljosipovic@ethz.ch | |
| Department | Information Technology and Electrical Engineering |
| Relationship | Assistant Professor (Tenure Track) |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 227-0085-69L | P&S: Let’s make ITET green!  Only for Electrical Engineering and Information Technology BSc. Course can only be registered for once. A repeatedly registration in a later semester is not chargeable. | 3 credits | 3P | G. Hug, L. Josipovic, K. Razavi | |||||||||||||||||||||||||||||
| Abstract | The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work. | ||||||||||||||||||||||||||||||||
| Learning objective | With the Net-Zero Programme (https://ethz.ch/en/the-eth-zurich/sustainability/net-zero.html) ETH wants to contribute to addressing climate change by reducing its own emissions. As one of the largest departments at ETH, D-ITET also needs to identify measures how as a department we can contribute to these goals. Thereby, it is important to take measures which are effective and have the highest potential for emissions and/or energy consumption reductions. In this P&S, the goal is to support the department in that regard and to quantify the effect of potential measures. Without specific numbers and a thorough analysis it is not possible to separate measures with negligible impact from such with major impact. The students are free to choose a specific measure that they would like to analyze. Examples of potential net-zero related measures include 1) assessing (by measurements and/or calculations) how much energy can be saved by temperature control in offices or turning off specific devices instead of keeping them in standby, 2) estimating how much energy could be produced by installing PV on all D-ITET buildings and how much of this can be used to supply the energy needs, 3) analyzing the power requirements and schedule of electrified vehicles using the charging stations of the department, 4) reporting power input requirements of D-ITET buildings (e.g., server rooms) and suggestions to improve their energy efficiency, 5) design auxiliary information of interest to building occupants, such as green features of their building, energy tips, the equivalent energy consumption (ex. Building ETL consumed x kWh, which could power the Eiffel Tower for y hours.) etc. At the end of the P&S, the students have not only learnt how to approach such questions but ideally are also in the position to recommend very specific measures to be implemented and actively promote sustainability in the department. There is also some budget available in case additional measurement equipment needs to be installed. Course day 1 (Lecture): 1.10.2024, 1pm to 3pm. Course day 2 (Lecture): 15.10.2024, 1pm to 3pm. Course day 3 (Students Presentations): 9.12.2024, 3pm to 5pm | ||||||||||||||||||||||||||||||||
| 227-0102-00L | Discrete Event Systems  | 6 credits | 4G | L. Vanbever, L. Josipovic, B. Keller, R. Wattenhofer | |||||||||||||||||||||||||||||
| Abstract | Introduction to discrete event systems. We start out by studying popular models of discrete event systems. Then we analyze discrete event systems from an average-case and from a worst-case perspective, and study verification. Topics include: Automata and Languages, Specification Models, Stochastic Discrete Event Systems, Worst-Case Event Systems, Verification, Petri Nets. | ||||||||||||||||||||||||||||||||
| Learning objective | Over the past few decades the rapid evolution of computing, communication, and information technologies has brought about the proliferation of new dynamic systems. A significant part of activity in these systems is governed by operational rules designed by humans. The dynamics of these systems are characterized by asynchronous occurrences of discrete events, some controlled (e.g. hitting a keyboard key, sending a message), some not (e.g. spontaneous failure, packet loss). The mathematical arsenal centered around differential equations that has been employed in systems engineering to model and study processes governed by the laws of nature is often inadequate or inappropriate for discrete event systems. The challenge is to develop new modeling frameworks, analysis techniques, design tools, testing methods, and optimization processes for this new generation of systems. In this lecture we give an introduction to discrete event systems. We start out the course by exploring the limits of what is computable and what is not. In doing so, we will consider three distinct models of computation which are often used to model discrete event systems: finite automata, push-down automata and Turing machines (ranked in terms of expressiveness power). In the second part of the course we analyze discrete event systems. We first examine discrete event systems from an average-case perspective: we model discrete events as stochastic processes, and then apply continuous time markov chains and queueing theory for an understanding of the typical behavior of a system. Then we analyze discrete event systems from a worst-case perspective using the theory of online algorithms and adversarial queueing. In the last part of the course we introduce methods that allow to formally verify certain properties of Finite Automata and Petri Nets. These are some typical analysis questions we will look at: Do two given systems behave the same? Does a given system behave as intended? Does the system eventually enter a dangerous state? | ||||||||||||||||||||||||||||||||
| Content | 1. Regular Languages 2. Non-Regular Languages 3. Markov Chains 4. Stochastic Discrete Event Systems 5. Worst-Case Event Systems 6. Verification of Finite Automata 7. Petri Nets | ||||||||||||||||||||||||||||||||
| Lecture notes | Available at https://disco.ethz.ch/courses/des/ | ||||||||||||||||||||||||||||||||
| Literature | [bertsekas] Data Networks Dimitri Bersekas, Robert Gallager Prentice Hall, 1991, ISBN: 0132009161 [borodin] Online Computation and Competitive Analysis Allan Borodin, Ran El-Yaniv. Cambridge University Press, 1998 [burch] Symbolic Model Checking J. R. Burch, E. M. Clarke, K. L. McMillan, D. L. Dill, and L. J. Hwang Inf. Comput. 98, 2 (June 1992), pp. 142-170 [boudec] Network Calculus J.-Y. Le Boudec, P. Thiran Springer, 2001 [cassandras] Introduction to Discrete Event Systems Christos Cassandras, Stéphane Lafortune. Kluwer Academic Publishers, 1999, ISBN 0-7923-8609-4 [fiat] Online Algorithms: The State of the Art A. Fiat and G. Woeginger [hochbaum] Approximation Algorithms for NP-hard Problems (Chapter 13 by S. Irani, A. Karlin) D. Hochbaum [murata] Petri Nets: Properties, Analysis and Applications Tadao Murata Proceedings of the IEEE, vol. 99, issue 4, April 1989. pp. 541-580 [schickinger] Diskrete Strukturen (Band 2: Wahrscheinlichkeitstheorie und Statistik) T. Schickinger, A. Steger Springer, Berlin, 2001 [sipser] Introduction to the Theory of Computation Michael Sipser. PWS Publishing Company, 1996, ISBN 053494728X | ||||||||||||||||||||||||||||||||
| Competencies |
| ||||||||||||||||||||||||||||||||