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EE454

Advanced Communication Networks

Description: This course covers the fundamentals of data communication networks. Specifically, the course explores: (i) analytical models that uncover challenges/tradeoffs of modern data networks, and (ii) mathematical techniques that enable performance evaluation and optimization.

 

Course objectives: When a student completes this course, s/he should be able to:

1. Describe the goals, functionalities, and trade-offs of the main components of a data communication network.

2. Model the main components of a communication network using concepts from Renewal Theory, Queueing Theory, Stochastic Control, and/or Mathematical Optimization.

3. Evaluate and optimize the performance of data communication networks using analytical methods.

 

Course topics:

  • Brief Review of Renewal Theory
  • Little’s Theorem
  • Queueing Theory (M/M/1, M/M/k/k, M/G/1, and others)
  • Network of Queues (Tandem Queues and Jackson Networks)
  • Multiple Access Techniques (ALOHA and Stability)
  • Wireless Transmission Scheduling (Graph Theory)
  • Max-Weight Transmission Scheduling (Lyapunov Optimization)
  • Optimal Routing (Spanning Trees and Dynamic Programming)
  • Backpressure Routing (Lyapunov Optimization)
  • Network Utility Maximization (Flow Control and Fairness)
  • Multi-Armed Bandits (Gittins and Whittle Indices)
  • Information Freshness (Age of Information in Wireless Networks)
  • System Implementation based on Mathematical Modeling

 

References:

Acknowledgement: the structure of this course was inspired both by the previous version of EE454 taught by Prof. Randall Berry and the MIT course 6.263 Data Communication Networks taught by Prof. Eytan Modiano.