CG4SR: Near Optimal Traffic Engineering for Segment Routing with Column Generation

Tue, 05/26/2020 - 13:40 by Olivier Bonaventure

Abstract

Segment Routing (SR) is a powerful tool to solve
traffic engineering in large networks. It enables steering the
traffic along any arbitrary network path while limiting scalability
issues as routers do not need to maintain a global state. Mathematical programming approaches proposed so far for SR either
do not scale well with the size of topology or impose a strong
limit on the number of possible detours (typically at most one).
Moreover they do not support Segment Routing fully by ignoring
the adjacency segments. This paper leverages column generation,
a widely used technique for solving large scale linear programs,
combined with a novel dynamic program for solving the pricing
problem. Our approach reaches near optimal solutions with gap
guarantees by also computing a strong lower-bound tighter than
the multi-commodity flow relaxation. It scales even on large
topologies and exploits the full expressiveness of SR including
adjacency segments. Our experiments compared with existing
traffic engineering techniques on various topologies and demand
matrices demonstrate the advantages of our approach in terms
of scalability, any-time behavior and quality of the solutions.

Authors
Mathieu Jadin, François Aubry, Pierre Schaus and Olivier Bonaventure
Source
INFOCOM, 2019.
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