  With the growth of demands for quasi-instantaneous communication services
such as real-time video streaming, cloud gaming, and industry 4.0 applications,
multi-constraint Traffic Engineering (TE) becomes increasingly important. While
legacy TE management planes have proven laborious to deploy, Segment Routing
(SR) drastically eases the deployment of TE paths and thus became the most
appropriate technology for many operators. The flexibility of SR sparked
demands in ways to compute more elaborate paths. In particular, there exists a
clear need in computing and deploying Delay-Constrained Least-Cost paths (DCLC)
for real-time applications requiring both low delay and high bandwidth routes.
However, most current DCLC solutions are heuristics not specifically tailored
for SR. In this work, we leverage both inherent limitations in the accuracy of
delay measurements and an operational constraint added by SR. We include these
characteristics in the design of BEST2COP, an exact but efficient ECMP-aware
algorithm that natively solves DCLC in SR domains. Through an extensive
performance evaluation, we first show that BEST2COP scales well even in large
random networks. In real networks having up to thousands of destinations, our
algorithm returns all DCLC solutions encoded as SR paths in way less than a
second.
