PENG9630 Internet Architecture and Measurements Emneplan

This course will give the student insight into the different parts that comprise the internet's architecture and how one can monitor, assess and characterise them. This involves a diverse set of topics that includes but is not limited to routing and addressing, content distribution, data centre networks, key services and application such as DNS and web and mobile broadband. The course will focus particularly on quantification of the robustness and reliability of the internet's architecture and services. Furthermore, the course will draw upon new advancments in the fields of machine learning and network science to extend and expand the toolset available for anlayzing Internet measurements.

The course will be offered once a year, provided 3 or more students sign up for the course. If less than 3 students sign up for a course, the course will be cancelled for that year.

The course will consist of six gatherings. Each gathering will contain a mixture of lectures and student presentation of relevant academic papers and cases. Each presentation will be followed by in-class discussions.

The student will write four reflection notes on ethical and sustainability issues. One of these will be related to their doctoral thesis project. One or more of the reflection notes may form a basis for inclusion as a section on ethical reflection in the student's final doctoral thesis.

None.

Knowledge

On successful completion of the course, the student:

• has an overview of the different elements that comprise the architecture of today’s internet.
• has a good understanding about the approaches for conducting internet measurements and the latest advances in this field.
• be familiar of a broad set of tools that can help analyzing Internet measurments. Of a particular relevance here are tools that originate in other disciplines like Machine Learning and Statisitcal Physics. This will not only expand the available toolset but also increases the potential for interdisciplinory collaboration going forward.

Skills

On successful completion of the course, the student can:

• plan and carry out state-of-the-art measurement tasks
• can formulate research questions on the robustness and performance of operational networks, and design measurements for evaluating these questions.
• will have a general practical understanding of how different parts of the internet's architecture interplay to offer a performant end-to-end service.

General competence

On successful completion of the course, the student can:

• participate in debates and present aspects of his/her expertise in a way that promotes such discussions.
• drive innovation

Module 1 will take the form of lectures. Module 2 will take the form of lab and homework assignments. Module 3 will take the form of seminars. In module 3, the student will present a case to the other students. We will also invite guest lecturers from research groups that focuses on machine learning and network science to introduce the students to potential tools and analysis methods.

Practical training

The students will participate in lab experiments to explore how once can measure various aspects of internet's robustness and performance. The students will write a summary of one of the tools that were introduced in the lab and discuss its benefits and limitations.

None.

Both the presentation of the case in Module 3 of the course and the tool summary document in the practical training part the course will form basis of assessment.

Both exams must be passed in order to pass the course.

The oral presentation cannot be appealed.

The goal of this course is to help students reflect over ethical dilemmas so that they make sound ethical choices throughout their doctoral studies and future careers. This course gives the students insight via relevant example projects from the spectrum of disciplines within engineering science including mathematics, physics, computer science, eletrical engineering, built engineerng and product design. Students will reflect on key philosophical questions related the explicit and implicit premises within their field as they relate to epistemology, methodology, ethics and history. The examples will expose the students to the full complexity of engineering projects, where ethical dilemmas and sustainability issues form the planning and execution of the project as well as the final product.

The course will be offered once a year, provided 3 or more students sign up for the course. If less than 3 students sign up for a course, the course will be cancelled for that year.

None.

Knowledge:

On successful completion of the course, the student:

• can account for the terminology and models related to ethics in engineering science
• has thorough knowledge of the requirements and standards for registration, processing, and storage of information about of participants in scientific research
• has a deep understanding of the role of scientific, societal and ethical values on their research.

Skills:

On successful completion of the course, the student can:

• present arguments and viewpoints relevant to ethical dilemmas prevalent in engineering science
• analyse and assess arguments relevant to ethics in engineering science in relation to their relevance and validity
• argue for solutions to ethical problems using theories and techniques relevant to engineering science
• deal with complex professional issues with an academic approach and reflect critically on established knowledge and practice in his/her own field in relation to sustainability, ethics and to other engineering disciplines
• reflect deeply on the nature of their research and its contribution to the production of knowledge

General competence:

On successful completion of the course, the student can:

• identify, discuss and reflect upon ethical and societal implications of his/her own research as well as of the applications they enable,
• reflect over values and ethical boundaries within engineering science