Networking for Big Data and Laboratory

Professor: Antonio Cianfrani & Andrea Baiocchi

Degree in: Master Degree in Data Science

Semester: II

Mailing listnbd2020@uniroma1.it

Lectures Time

Academyc Year 2020-2021

Monday 15:00 - 17:00 (Room B2 - DIAG - via Ariosto)

Tuesday 15:00 - 19:00 (Room 15 - CU035 - Main Campus)

Friday 12:00-14:00 (Room 15 - CU035 - Main Campus)

 

The students can join the lectures in person (using the PRODIGIT tool for reservation) or online using Zoom.

----------------------------------------------------------------------------------------------------------------------

The Zoom parameters for the lectures of Prof. Cianfrani are:

Link: https://uniroma1.zoom.us/j/88236804152?pwd=em4zZGJ3UzEvRXZ6eGtiUE1iZHNNZz09

Meeting ID: 882 3680 4152

Passcode: 108258

----------------------------------------------------------------------------------------------------------------------

The Zoom parameters for the lectures of Prof. Baiocchi (starting Tuesday, March 9) are:

Link: https://uniroma1.zoom.us/j/83819073579?pwd=YUc1MWNBajh4REZpemExSXo3Q1loUT09

Meeting ID: 838 1907 3579

Passcode: 727621

----------------------------------------------------------------------------------------------------------------------

 

Office Hours

Prof. Antonio Cianfrani - Office hours will take place on Thursday from 3 pm to 4 pm. It is possible to fix videocalls in different days sending an email to antonio.cianfrani@uniroma1.it

Prof. Andrea Baiocchi - Office hours will be provided online on Monday morning (from 11:00 to 12:00). It is possible to arrange dedicated Skype calls sending an email to andrea.baiocchi@uniroma1.it

Prerequisite

A basic understanding of programming logic. Basics of probability and statistics. Basics of matrix algebra.

 

Outline of the Course

Module 1. NETWORKING FUNDAMENTALS

- TCP/IP protocol stack

- Transport layer: TCP and UDP

- IP layer: addressing and routing

- Link layer: forwarding

- Virtual LAN (VLAN)

- Virtual eXtensible LAN (VXLAN)

- Locator/Identifier Separation Protocol (LISP)

- Software Defined Networking (SDN) 

- Network Monitoring (IPFIX)

- Application layer: HTTP and DNS

- Lab activity: IP network emulator (Netkit) and packet sniffing (Wireshark)

 

Module 2. DATA CENTERS

- Outline of cloud computing.

- Data centers architectures, topologies, addressing, routing.

- Job scheduling and load balancing.

- Congestion control (QCN, DCTCP).

Course Object

The first aim of the Networking for Big Data and Laboratory course is to provide students the principles of Internet networking. The course also focuses on recent advances in networking protocols to efficiently support Distributed Data Centers infrastructures. Finally, Data Center architecture is presented and two major issues are investiaged with some detail, namely scheduling and congestion control. The course has also a practical part, mainly devoted to IP and SDN networks configuration and troubleshooting.

 

Teaching Material

 
Slide 
 

 

Schedule of classes, slides and bibliographic material for the Data Center module of NBD can be found here.

 
Exercitations
   

 

Laboratory
   

 

Bibliography

James F. Kurose and Keith Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, Pearson

Netkit Emulator, Netkit Documentation page

Additional material provided by the lecturer on the Data Centers

VXLAN Technical Report

LISP protocol (pages 23-36)

Software Defined Networking - a survey

 

 

© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma