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

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)

 

!!!!!!!! NEWS !!!!!!!!!!

Starting from March 13th 2020 till the end of the suspension of the physical lectures, the classes of Networking for Big Data and Laboratory will move online (with the same time scheduling of physical lectures). The platform used for real time video lectures is Webex. The students will receive all the information for the connection to the Webex platform via the course mailing list. The recorded lectures will be available on the virtual class created on the Classroom tool, provided by Google and accessible using the institutional mail. The virtual class course codes are: (i) jpp4skn for the Google Classroom of Prof. Cianfrani; (ii) ygwpyda for the Google Classroom of Prof. Baiocchi.

Office Hours

Prof. Antonio Cianfrani - Office hours will be provided online on Wednesday morning (from 11:00 to 12:00). It is possible to fix dedicated calls (using Skype or Webex) 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 
Course Introduction
TCP/IP protocol stack
The Transport Layer
TCP
The Network Layer
The Data Link Layer

 

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

 
Exercitations
Exercise IP subnetting

 

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

 

 

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