Babes-Bolyai University of Cluj-Napoca
Faculty of Mathematics and Computer Science
Study Cycle: Graduate
SUBJECT

Code	Subject	
MIC0009	Congestion Management in Computer Networks	

Section	Semester	Hours: C+S+L	Category	Type	
Computer Science - in English	5	2+0+2	speciality	optional	

Teaching Staff in Charge	Lect. BUFNEA Darius Vasile, Ph.D., bufny@cs.ubbcluj.ro	
Aims	The Congestion Management in Computer Networks class prepares the students to deal with congestion as a negative phenomenon that affects the working performance of the Internet. Students, as future system or network administrators must acquire specific knowledge to successfully identify congestion causes and apply best practice methods to reduce congestion consequences. As future software developers, students must learn how to design and implement healthy Internet communication protocols that must be congestion aware when interact with congestion affected areas.	
Content	- Congestion as a negative phenomenon that affects the Internet. Congestion types.
- Main causes of Internet congestion.
- Implicit congestion notification using packet dropping. Explicit congestion notification using the ECN header bit filed.
- Congestion control at the transport protocol level. TCP congestion control protocol. Slow start algorithm.
- TCP congestion control inside the Linux TCP/IP stack.
- Congestion control at the transport level. Active queue management control algorithms. RED algorithm. Per flow scheduling.
- Binomial congestion control algorithms. Congestion control for multimedia streams. Constraints regarding the congestion control of multimedia streams.
- Congestion managers. Congestion control inside a congestion manager. Macroflows. Nature of a macroflow and its granularity.
- Fine-grained macroflow granularity at the stream&#8217;s source level.
- Fine-grained macroflow granularity from the receiver&#8217;s perspective.
	
Bibliography	- Jacobson, V., Congestion Avoidance and Control, Proceedings of SIGCOMM 88, Stanford, CA, August 1988, ACM.
- Floyd, S., Jacobson, V., Random Early Detection Gateways for Congestion Avoidance, IEEE/ACM Transactions on Networking, 1(4), pp. 379-413, 1993.
- Floyd, S. and Fall, K., Promoting the Use of End-to-End Congestion Control in the Internet, IEEE/ACM Transactions on Networking, Vol. 7, No. 4, pp. 458-472, 1999.
- Balakrishnan, H., Seshan, S. The Congestion Manager, IETF RFC 3124, June 2001.
- Sarolahti, P., Kuznetsov, A., Congestion Control in Linux TCP, Proceedings of USENIX 2002/Freenix Track, pp. 49-62. Monterey, CA, USA, June 2002.
- Bufnea, D. V., Campan, A., Darabant, A.S., Fine-Grained Macroflow Granularity in Congestion Control Management, in Studia Universitatis, Vol. L(1), pp. 79-88, 2005.
- Campan, A., Bufnea, D. V., Delimitation of Macroflows in Congestion Control Management Using Data Mining Techniques, 4th ROEDUNET International Conference, Education/Training and Information/Communication Technologies - ROEDUNET @05, Romania, pp. 225-234, 2005.
- Brown, M. A., Traffic Control using tcng and HTB, http://tldp.org/HOWTO/Traffic-Control-tcng-HTB-HOWTO/, April 2006.
- Bufnea, D., Controlul si optimizarea traficului in retele de calculatoare, PhD Thesis, 2007.
- Bufnea, D. V., A New Method for Macroflows Delimitation from a Receiver@s Perspective, in the International Journal of Computer, Communication & Control - proceedings of the IEEE 2nd International Conference on Computers, Communications & Control (ICCCC 2008), Felix Spa, Romania, Vol. III (2008), pp. 201-205.	
Assessment	The activity ends with a written exam (grade E). During the semester, the students will prepare several lab projects (grade L). The final grade is the average of the above grades: Final Grade = 50%E + 50%L. In order to successfully pass the exam, the final grade and each of its components have to be at least 5.