PENG9630 Internettarkitektur og målinger 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.

Basic background in computer science and networking.

Cloud computing is an emerging paradigm of utilising large-scale computing services over the internet that will affect the computing needs of individuals and organisations. Over the past decade, many cloud computing platforms have been set up by companies such as Google, Yahoo!, Amazon, Microsoft, Salesforce, eBay and Facebook. Some of the platforms are open to the public via various pricing models. They operate at different levels and enable businesses to harness different amounts of computing power from the cloud.

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.

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

The course describes the important enabling technologies of cloud computing, explores state- of-the art platforms and existing services, and examines the challenges and opportunities of adopting cloud computing. Moreover, the course investigates how to protect the critical data increasingly being stored in the cloud. The students learn how to build a security strategy that keeps data safe and mitigates risk.

The course is part of a series of seminars in which the students actively participate together with members of relevant research groups. The students present papers and listen to paper presentations from other PhD students and staff. The students are also expected to actively critique and challenge fellow participants. The students are provided with a sound foundation in research skills and are naturally integrated into the local research community and its research discourse.

The following required coursework must be approved before the student can take the exam:

• Three individual oral presentations of assigned publications.
• Participate as prepared discussant for three presentations by other group members.
• Independently find and study publications relevant to the research discourse.
• 80% attendance at seminars.

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.

None.

Pass or fail.

Two sensors, one from the teaching staff, the other may be internal or external. External examiner is used periodically.