G2: A Network Optimization Framework for High-Precision Analysis of Bottleneck and Flow Performance
Jordi Ros-Giralt, Sruthi Yellamraju, Atul Bohara, Richard Lethin, Josie Li, Ying Lin, Yuanlong Tan, Malathi Veeraraghavan, Yuang Jiang, Leandros Tassiulas · 2019
Congestion control algorithms for data networks have been the subject of intense research for the last three decades. While most of the work has focused around the characterization of a flow's bottleneck link, understanding the interactions amongst links and the ripple effects that perturbations in a link can cause on the rest of the network has remained much less understood. The Theory of Bottleneck Ordering is a recently developed mathematical framework that reveals the bottleneck structure of a network and provides a model to understand such effects. In this paper we present G2, the first operational network optimization framework that utilizes this new theoretical framework to characterize with high-precision the performance of bottlenecks and flows. G2 generates an interactive graph structure that describes how perturbations in links and flows propagate, providing operators new optimization insights and traffic engineering recommendations to help improve network performance. We provide a description of the G2 implementation and a set of experiments using production TCP/IP code to demonstrate its operational efficacy.