Courses / DescriptionsEECS 454: Advanced Communication Networks
Quarter OfferedNone ;
PrerequisitesA good understanding of basic probability (e.g. EECS 302). Introductory knowledge of communication networks (e.g. EECS 333 or 340) is also helpful, but not require
CATALOG DESCRIPTION: Basic techniques for modeling and analyzing communication networks. Fairness and utility functions, routing, congestion control, pricing, queuing models, loss networks, multi-class queues and scheduling.
REQUIRED TEXTBOOK: None.
- D. Bertsekas and R. Gallager, Data Networks, Prentie Hall, 2nd edition, 1992
- B. Hajek, Notes for ECE 567: Communication Network Analysis, available on-line
- Selected Journal Articles and supplementary notes.
COURSE INSTRUCTOR: Prof. Dongning Guo
COURSE COORDINATOR: Prof. Randall Berry
COURSE GOALS: The goal of this class is to develop understanding of some fundamental techniques used to model and analyze communication networks. Compared to EECS 333 or 340, the emphasis in this course will be more on developing analytical tools and conceptual models and less on describing the protocols used in current networks. However, some current protocols will be used to illustrate the concepts. These analytical tools are used to analyze the performance of various networks. More importantly, understanding this material can help one to develop intuition about some of the important issues in networking and provide the background needed to do research in this field.
- A good understanding of basic probability (e.g. EECS 302).
- Introductory knowledge of communication networks (e.g. EECS 333 or 340) is also helpful, but not require
DETAILED COURSE TOPICS:
- Fairness and network utility maximization
- Optimization based routing and congestion control
- Basic queueing models and their application to switching and scheduling in networks.
HOMEWORK ASSIGNMENTS: The course will have quasi-weekly homework assignments as well as a final project that will be based on reading and reviewing one or more current papers related to the course topics.
- Homeworks – 25%
- Exams – 50%
- Final Project – 25%
COURSE OBJECTIVES: When a student completes this course, s/he should be able to:
- Understand the analytical tools and conceptual models used in network performance analysis.
- Undertake research in network performance analysis.