  Many state-of-the-art Segment Routing (SR) Traffic Engineering (TE)
algorithms rely on Linear Program (LP)-based optimization. However, the poor
scalability of the latter and the resulting high computation times impose
severe restrictions on the practical usability of such approaches for many use
cases. To tackle this problem, a variety of preprocessing approaches have been
proposed that aim to reduce computational complexity by preemtively limiting
the number of SR paths to consider during optimization. In this paper, we
provide the first extensive literature review of existing preprocessing
approaches for SR. Based on this, we conduct a large scale comparative study
using various real-world topologies, including recent data from a Tier-1
Internet Service Provider (ISP) backbone. Based on the insights obtained from
this evaluation, we finally propose a combination of multiple preprocessing
approaches and show that this can reliably reduce computation times by around a
factor of 10 or more, without resulting in relevant deterioration of the
solution quality. This is a major improvement over the current state-of-the-art
and facilitates the reliable usability of LP-based optimization for large
segment-routed networks.
