Timothy Roscoe: Catalogue data in Spring Semester 2018

Award: The Golden Owl
Name Prof. Dr. Timothy Roscoe
FieldInformatik
Address
Institut für Computing Platforms
ETH Zürich, STF H 314
Stampfenbachstrasse 114
8092 Zürich
SWITZERLAND
Telephone+41 44 632 88 40
E-mailtroscoe@inf.ethz.ch
URLhttp://people.inf.ethz.ch/troscoe/
DepartmentComputer Science
RelationshipFull Professor

NumberTitleECTSHoursLecturers
252-0817-00LDistributed Systems Laboratory Information
In the Master Programme max. 10 credits can be accounted by Labs
on top of the Interfocus Courses. Additional Labs will be listed on the Addendum.
10 credits9PG. Alonso, T. Hoefler, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang
AbstractThis 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 mobile phones.
ObjectiveStudents acquire practical knowledge about technologies from the area of distributed systems.
ContentThis 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 mobile phones. The objecte 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, please contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso.
263-3830-00LSoftware Defined Networking: The Data Centre Perspective Information 2 credits2ST. Roscoe, D. Wagenknecht-Dimitrova
AbstractSoftware 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.
ObjectiveThrough 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.
ContentSoftware 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.
LiteratureThe 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.
Prerequisites / NoticeThe seminar bases on active and interactive participation of the students.
851-0740-00LBig Data, Law, and Policy Restricted registration - show details
Number of participants limited to 35

Students will be informed by 4.3.2018 at the latest
3 credits2SS. Bechtold, T. Roscoe, E. Vayena
AbstractThis 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.
ObjectiveThis 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) Restricted registration - show details
Limited number of participants.

Students will be informed by 4.3.2018 at the latest
6 credits2S + 2AS. Bechtold, T. Roscoe, E. Vayena
AbstractThis 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.
ObjectiveThis 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.