Friedemann Mattern: Catalogue data in Autumn Semester 2019 |
| Name | Prof. em. Dr. Friedemann Mattern |
| Field | Informatik |
| Address | Zasiusstr. 111 79102 Freiburg GERMANY |
| Telephone | +49 761 70766547 |
| mattern@inf.ethz.ch | |
| URL | http://people.inf.ethz.ch/mattern/ |
| Department | Computer Science |
| Relationship | Professor emeritus |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 252-0437-00L | Distributed Algorithms  Does not take place this semester. | 5 credits | 3V + 1A | F. Mattern | |
| Abstract | Models of distributed computations, time space diagrams, virtual time, logical clocks and causality, wave algorithms, parallel and distributed graph traversal, consistent snapshots, mutual exclusion, election and symmetry breaking, distributed termination detection, garbage collection in distributed systems, monitoring distributed systems, global predicates. | ||||
| Learning objective | Become acquainted with models and algorithms for distributed systems. | ||||
| Content | Verteilte Algorithmen sind Verfahren, die dadurch charakterisiert sind, dass mehrere autonome Prozesse gleichzeitig Teile eines gemeinsamen Problems in kooperativer Weise bearbeiten und der dabei erforderliche Informationsaustausch ausschliesslich über Nachrichten erfolgt. Derartige Algorithmen kommen im Rahmen verteilter Systeme zum Einsatz, bei denen kein gemeinsamer Speicher existiert und die Übertragungszeit von Nachrichten i.a. nicht vernachlässigt werden kann. Da dabei kein Prozess eine aktuelle konsistente Sicht des globalen Zustands besitzt, führt dies zu interessanten Problemen. Im einzelnen werden u.a. folgende Themen behandelt: Modelle verteilter Berechnungen; Raum-Zeit Diagramme; Virtuelle Zeit; Logische Uhren und Kausalität; Wellenalgorithmen; Verteilte und parallele Graphtraversierung; Berechnung konsistenter Schnappschüsse; Wechselseitiger Ausschluss; Election und Symmetriebrechung; Verteilte Terminierung; Garbage-Collection in verteilten Systemen; Beobachten verteilter Systeme; Berechnung globaler Prädikate. | ||||
| Literature | - F. Mattern: Verteilte Basisalgorithmen, Springer-Verlag - G. Tel: Topics in Distributed Algorithms, Cambridge University Press - G. Tel: Introduction to Distributed Algorithms, Cambridge University Press, 2nd edition - A.D. Kshemkalyani, M. Singhal: Distributed Computing, Cambridge University Press - N. Lynch: Distributed Algorithms, Morgan Kaufmann Publ | ||||
| 252-0817-00L | Distributed Systems Laboratory In the Master Programme max.10 credits can be accounted by Labs on top of the Interfocus Courses. These Labs will only count towards the Master Programme. Additional Labs will be listed on the Addendum. | 10 credits | 9P | G. Alonso, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang | |
| Abstract | This course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including wireless networks, ad-hoc networks, RFID, and distributed applications on smartphones. | ||||
| Learning objective | Gain hands-on-experience with real products and the latest technology in distributed systems. | ||||
| Content | This course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on smartphones. The goal of the project is for the students to gain hands-on-experience with real products and the latest technology in distributed systems. There is no lecture associated to the course. For information of the course or projects available, see https://www.dsl.inf.ethz.ch/ or contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso. | ||||
| 252-0836-00L | Computer Science II | 4 credits | 2V + 1U | F. Mattern | |
| Abstract | Introduction to basic problem solving methods, algorithms, and data structures. Topics: divide and conquer, recursion, sorting algorithms, backtracking, game tree search, data structures (lists, stacks, binary trees, etc.), discrete simulation, concurrency, complexity, verification. In the assignments and exercises, the programming language Java is used. | ||||
| Learning objective | Introduction to the general methods of computer science for electrical engineers. Also provides basic skills for advanced exercises and projects later in the electrical engineering program. | ||||
| Content | Part II of the lecture concentrates on the most common problem solving skills, algorithms, and data structures. It also teaches fundamental concepts and mechanisms of structured programming. Furthermore, working with formal systems, the necessity of abstraction, and the importance of modeling in computer science will be motivated. The emphasis of the lecture is on practical concepts of computer science. Specific topics are: complexity and correctness of algorithms, divide and conquer, recursion, algorithms for sorting, backtracking, game tree search, data structures (lists, stacks, inary trees, etc.), discrete simulation, concurrency, and verification. For the assignments and exercises, the programming language Java is used. Here, also modularization, abstraction, encapsulation, and object orientation will be considered. Occasionally, short remarks on the historical context of relevant concepts are given. In the practice groups, students program an automatic player for the game "Reversi"; at the end of the semester a tournament will take place. | ||||
| Lecture notes | Copies of slides, extended with bonus slides that give hints to advanced concepts and present the historical context of selected concepts. | ||||
| Literature | Textbook: Mark Allan Weiss: Data Structures and Problem Solving Using Java, Addison Wesley. | ||||
| Prerequisites / Notice | Prerequisite: Part 1 of the course. | ||||
| 252-3610-00L | Smart Energy | 4 credits | 2G + 1A | F. Mattern, V. C. Coroama | |
| Abstract | The lecture covers the role of ICT for sustainable energy usage. It starts out with a general background on the current landscape of energy generation and consumption and outlines concepts of the emerging smart grid. The lecture combines technologies from ubiquitous computing and traditional ICT with socio-economic and behavioral aspects and illustrates them with examples from actual applications. | ||||
| Learning objective | Participants become familiar with the diverse challenges related to sustainable energy usage, understand the principles of a smart grid infrastructure and its applications, know the role of ubiquitous computing technologies, can explain the challenges regarding security and privacy, can reflect on the basic cues to induce changes in consumer behavior, develop a general understanding of the effects of a smart grid infrastructure on energy efficiency. Participants will apply the learnings in a course-accompanying project, which includes both programming and data analysis. The lecture further includes interactive exercises, case studies and practical examples. | ||||
| Content | - Background on energy generation and consumption; characteristics, potential, and limitations of renewable energy sources - Introduction to energy economics - Smart grid and smart metering infrastructures, virtual power plants, security challenges - Demand management and home automation using ubiquitous computing technologies - Changing consumer behavior with smart ICT - Benefits and challenges of a smart energy system - Smart heating, electric mobility | ||||
| Literature | Will be provided during the course, though a good starting point is "ICT for green: how computers can help us to conserve energy" from Friedemann Mattern, Thosten Staake, and Markus Weiss (available at http://www.vs.inf.ethz.ch/publ/papers/ICT-for-Green.pdf). | ||||