Timothy Roscoe: Katalogdaten im Frühjahrssemester 2018

Auszeichnung: Die Goldene Eule
NameHerr Prof. Dr. Timothy Roscoe
LehrgebietInformatik
Adresse
Institut für Computing Platforms
ETH Zürich, STF H 314
Stampfenbachstrasse 114
8092 Zürich
SWITZERLAND
Telefon+41 44 632 88 40
E-Mailtroscoe@inf.ethz.ch
URLhttp://people.inf.ethz.ch/troscoe/
DepartementInformatik
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
252-0817-00LDistributed Systems Laboratory Information
Im Masterstudium können zusätzlich zu den Vertiefungsübergreifenden Fächern nur max. 10 Kreditpunkte über Laboratorien erarbeitet werden. Weitere Laboratorien werden auf dem Beiblatt aufgeführt.
10 KP9PG. Alonso, T. Hoefler, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang
KurzbeschreibungEntwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme. Das Projekt kann aus unterschiedlichen Teilbereichen (von Web-Services bis hin zu ubiquitären Systemen) stammen; typische Technologien umfassen drahtlose Ad-hoc-Netze oder Anwendungen auf Mobiltelefonen.
LernzielErwerb praktischer Kenntnisse bei Entwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme.
InhaltEntwicklung und / oder Evaluation eines umfangreicheren praktischen Systems mit Technologien aus dem Gebiet der verteilten Systeme. Das Projekt kann aus unterschiedlichen Teilbereichen (von Web-Services bis hin zu ubiquitären Systemen) stammen; typische Technologien umfassen drahtlose Ad-hoc-Netze oder Anwendungen auf Mobiltelefonen. Zu diesem Praktikum existiert keine Vorlesung. Bei Interesse bitte einen der beteiligten Professoren oder einen Assistenten der Forschungsgruppen kontaktieren.
263-3830-00LSoftware Defined Networking: The Data Centre Perspective Information 2 KP2ST. Roscoe, D. Wagenknecht-Dimitrova
KurzbeschreibungSoftware Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done.
LernzielThrough review and discussion of literature on an exciting new trend in networking, the students get the opportunity to get familiar with one of the most promising new developments in data centre connectivity, while at the same time they can develop soft skills related to the evaluation and presentation of professional content.
InhaltSoftware Defined Networks (SDN) is a change supported not only by research but also industry and redifens how traditional network management and configuration is been done. Although much has been already investigated and there are already functional SDN-enabled switches there are many open questions ahead of the adoption of SDN inside and outside the data centre (traditional or cloud-based). With a series of seminars we will reflect on the challenges, adoption strategies and future trends of SDN to create an understanding how SDN is affecting the network operators' industry.
LiteraturThe seminar is based on recent publications by academia and industry. Links to the publications are placed on the Seminar page and can be downloaded from any location with access to the ETH campus network.
Voraussetzungen / BesonderesThe seminar bases on active and interactive participation of the students.
851-0740-00LBig Data, Law, and Policy Belegung eingeschränkt - Details anzeigen
Number of participants limited to 35

Students will be informed by 4.3.2018 at the latest
3 KP2SS. Bechtold, T. Roscoe, E. Vayena
KurzbeschreibungThis course introduces students to societal perspectives on the big data revolution. Discussing important contributions from machine learning and data science, the course explores their legal, economic, ethical, and political implications in the past, present, and future.
LernzielThis course is intended both for students of machine learning and data science who want to reflect on the societal implications of their field, and for students from other disciplines who want to explore the societal impact of data sciences. The course will first discuss some of the methodological foundations of machine learning, followed by a discussion of research papers and real-world applications where big data and societal values may clash. Potential topics include the implications of big data for privacy, liability, insurance, health systems, voting, and democratic institutions, as well as the use of predictive algorithms for price discrimination and the criminal justice system. Guest speakers, weekly readings and reaction papers ensure a lively debate among participants from various backgrounds.
860-0018-00LBig Data, Law, and Policy (with Case Study) Belegung eingeschränkt - Details anzeigen
Limited number of participants.

Students will be informed by 4.3.2018 at the latest
6 KP2S + 2AS. Bechtold, T. Roscoe, E. Vayena
KurzbeschreibungThis course examines and critiques the design of the Internet, with a focus on the connection between the engineering features and principles of the network and the legal, economic, and political concerns which have followed its evolution.
LernzielThis course examines and critiques the design of the Internet (broadly defined), with a focus on the connection between the engineering features and principles of the network (packet switching, global addressing, the end-to-end argument, etc.) and the legal, economic, and political concerns which have followed its evolution (security properties, censorship and censorship resistance, "net neutrality", etc.). No prior knowledge of networking technologies is required; conversely the course will focus only on those features of the Internet design which have strong political and legal implications (and vice versa). The course consists of two parts: lectures and seminars in one part provide an introduction and discussion of the technical, legal, and political aspects of the Internet design. The other part consists of a specific case study of some aspect of the Internet by individual students.