Networking for Big Data and Laboratory
Professor: Antonio Cianfrani & Andrea Baiocchi
Degree in: Master Degree in Data Science
Mailing list: firstname.lastname@example.org
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.
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 email@example.com
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 firstname.lastname@example.org
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).
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.
|TCP/IP protocol stack|
|The Transport Layer|
|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.
|Exercise IP subnetting|
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