| KEYWORD |
Big Data Performance Monitoring of IP Networks
Thesis in external company
keywords BIG DATA, NETWORK MONITORING
Reference persons GUIDO MARCHETTO, RICCARDO SISTO
Research Groups COMPUTER NETWORKS GROUP - NETGROUP, DAUIN - GR-03 - COMPUTER NETWORKS GROUP - NETGROUP, GR-03 - COMPUTER NETWORKS GROUP - NETGROUP, NETGROUP
Thesis type EXPEIRMENTAL, IN COMPANY
Description Performance monitoring of IP networks is of great importance for service providers because it allows them to manage Service Level Agreements (SLA) with internal and external customers.
In this context, one of the problems that are being addressed is the scalability of passive monitoring systems: if, for example, we want to monitor thousands of flows, it is necessary that each one of them is filtered by a specific capture rule loaded into each monitoring point. The problem that arises is that network devices support only a limited number of such rules, thus limiting the number of flows that can be monitored.
In order to solve this issue, it is possible to introduce the concept of multipoint flow, which groups together a set of elementary flows. Then, a smaller number of multipoint flows is monitored, instead of all the elementary flows of interest.
The data so captured, can then be processed in order to extract more precise information, e.g. referred to single elementary flows or certain subsets of elementary flows.
From a theoretical point of view, the way of defining multipoint flows and the above mentioned post-processing operations have been defined in a patent held by Telecom Italia.
In the context of previous theses, an architecture has also been defined to implement this technique where certain probes installed in the network capture traffic, the captures are collected in a database, and the captured data are analyzed by post-processing software capable of extracting the necessary information starting from those contained in the DB. Since the size of the monitoring data can be considerable, the architecture adopts solutions for big data such as Hadoop, Flume and Kafka. The purpose of the thesis, to be developed at Telecom Italia, is to continue this project in one of several possible directions, such as introducing artificial intelligence techniques for the automatic analysis of the data collected in the DB or improving aspects such as usability and efficiency. of the current framework.
Required skills Reti IP, Programmazione di Rete, Database, Interazione con DB remoti
Deadline 26/02/2022
PROPONI LA TUA CANDIDATURA