Network Measurements and Traffic Monitoring

The importance of mobile Internet access in our society is steadily growing, as more physical objects get connected (Internet of Things) and an increasing share of our daily activities rely on smartphones and apps. Ubiquitous and reliable connectivity is provided to the end-users by a “network of networks”, i.e., a global system composed of the interconnection of multiple IP network infrastructures, wired and wireless, owned and managed by different players (network operators). The scale and complexity of the network infrastructure is growing together with the requirements for reliability and performances. Owing to the ever-evolving nature of such network infrastructures, the risk of failures and performance degradation caused by accidental faults and/or deliberate attacks is not decreasing. As with any complex infrastructure, the network needs to be continuously monitored in order to promptly identify (and resolve) problems, failures and any sort of anomalous behavior. 

The course focuses on methods and techniques to measure the performances of a packet-oriented network in order to reveal performance degradation and faults in wide-area networks. Particular focus is given to wireless mobile networks (3G/4G).

The goal of the course is to provide the student with an understanding of the most important aspects that must be considered in all phases of the monitoring process, from the design of the data collection methodology to the representation, analysis and interpretation of the measurement data. Some fundamental theoretical aspects of data analytics will be discussed along with more practical “do and don’t” rules. During the course, several case-study problems from real-world measurement activities and research problems will be critically examined and discussed in the classroom, in order to distill general guidelines and data properties in a bottom-up fashion.

The course is useful also for PhD students that are working in different research areas. In fact, the analysis of data from a dynamic, heterogeneous and complex system like “the Internet” leads naturally to encounter a number of concepts and system-level aspects that are very general and apply to many other engineered systems.

In summary, the methods and skills acquired by the students during the project will benefit the students along multiple directions:

1.      Students will gain a more in-depth understanding of the dynamics at play in real-world networks.

2.    Based on the methods and skills acquired during the course, the students will be able to engage in research activities related to measuring and analyzing datasets from computer networks.

3.    Several notions and ideas presented during the course with reference to packet networks are actually much more general, and apply mutatis mutandis to other classes of large-scale systems in other domains.

Examination: verbal colloquium and project assignment.