Abstract
The well-known Additive Increase-Multiplicative Decrease (AIMD) abstraction for network congestion control was first published by Dah-Ming Chiu and Raj Jain in their seminal work [4] in 1989 and soon played a prominent part in TCP algorithm design for the Internet. The ingenuity of AIMD lies in the abstraction of Internet congestion control, and ever since its inception has also been a staple part of teaching curriculum for performance evaluation and computer networking courses at universities worldwide. In this paper, we describe teaching examples for university students to appreciate the AIMD abstraction from the theoretical aspects such as convex optimization and Perron-Frobenius theory to the data science aspect. The essence of cooperation encompassed by AIMD reverberates even in teaching networks formed by students and educators, giving rise to online classroom flipping teaching tools and data analytics to close the gap between teachers and students.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
