Contributing Scholars - Muriel Medard and Dina Katabi, MIT

3 Semester Credit Hours

Course Description

This is a first class on the fundamentals of data communication networks, their architecture, principles of operations, and performance analyses. Students are expected to have a strong mathematical background and an understanding of probability theory.

Prerequisites

• Probabilistic Systems Analysis or equivalent
• General prerequisite: Students must have the knowledge resulting from completing all coursework in the curriculum for a BS degree in Computer Science from a regionally-accredited institution in the United States or the equivalent from a foreign institution; performance level in this coursework should be equivalent to a cumulative undergraduate GPA of 2.9 or better on 4.0 scale.

Course Objectives

This course will provide insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the class will focus on network algorithms and their performance. Topics discussed will include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues including routing and flow control.

Course Topics

The following topics will be covered in the order given.

• Designing Computer Networks
• Markov Chains, Queues, Little's Law
• M/M/... Queues
• M/G/... Queues, Use of Transforms
• Networks, Reversibility
• ALOHA and Collision Issues
• Wireless Medium Access Control
• Intra-Domain Routing
• Inter-Domain Routing
• Content-Based Routing & Distributed Hash Tables (DHTs) 
• Multicast
• Optimal Routing
• Traffic Engineering
• Routing for Recovery
• Overview of Switching, Basic Switching Theory
• Matching and Stability Issues
• TCP
• Router-Aided Congestion Control
• Basics of Point-to-Point Coding