Big Data for Traffic Monitoring and Management

by   Martino Trevisan, et al.

The last two decades witnessed tremendous advances in the Information and Communications Technologies. Beside improvements in computational power and storage capacity, communication networks carry nowadays an amount of data which was not envisaged only few years ago. Together with their pervasiveness, network complexity increased at the same pace, leaving operators and researchers with few instruments to understand what happens in the networks, and, on the global scale, on the Internet. Fortunately, recent advances in data science and machine learning come to the rescue of network analysts, and allow analyses with a level of complexity and spatial/temporal scope not possible only 10 years ago. In my thesis, I take the perspective of an Internet Service Provider (ISP), and illustrate challenges and possibilities of analyzing the traffic coming from modern operational networks. I make use of big data and machine learning algorithms, and apply them to datasets coming from passive measurements of ISP and University Campus networks. The marriage between data science and network measurements is complicated by the complexity of machine learning algorithms, and by the intrinsic multi-dimensionality and variability of this kind of data. As such, my work proposes and evaluates novel techniques, inspired from popular machine learning approaches, but carefully tailored to operate with network traffic.




Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service

Recently, we have been witnessing huge advancements in the scale of data...

A Survey on Big Data for Network Traffic Monitoring and Analysis

Network Traffic Monitoring and Analysis (NTMA) represents a key componen...

Big Issues for Big Data: challenges for critical spatial data analytics

In this paper we consider some of the issues of working with big data an...

Run Time Prediction for Big Data Iterative ML Algorithms: a KMeans case study

Data science and machine learning algorithms running on big data infrast...

Data Science Methodology for Cybersecurity Projects

Cyber-security solutions are traditionally static and signature-based. T...

Modeling Activation Processes in Human Memory to Improve Tag Recommendations

This thesis was submitted by Dr. Dominik Kowald to the Institute of Inte...

Deep Neural Mobile Networking

The next generation of mobile networks is set to become increasingly com...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.