Networking for Big Data and Laboratory

Professor: Antonio Cianfrani & Andrea Baiocchi

Degree in: Master Degree in Data Science

Semester: II

Mailing list

Lectures Time

Academyc Year 2021-2022

  • Monday 15:00 - 17:00 (classroom B2 - building RM102 - via Ariosto 25)

  • Tuesday 15:00 - 19:00 (classroom 15 - building CU035 - piazzale Aldo Moro 5)

  • Friday 12:00 - 14:00 (classroom 15 - building CU035 - piazzale Aldo Moro 5)

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

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

 

Course website Moodle (Prof. Cianfrani)https://elearning.uniroma1.it/course/view.php?id=14634

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

The Zoom parameters for the lectures of Prof. Baiocchi :

Link: 

Meeting ID: 

Passcode: 

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

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