  In backbone networks, it is fundamental to quickly protect traffic against
any unexpected event, such as failures or congestions, which may impact Quality
of Service (QoS). Standard solutions based on Segment Routing (SR), such as
Topology-Independent Loop-Free Alternate (TI-LFA), are used in practice to
handle failures, but no distributed solutions exist for distributed and
tactical congestion mitigation. A promising approach leveraging SR has been
recently proposed to quickly steer traffic away from congested links over
alternative paths. As the pre-computation of alternative paths plays a
paramount role to efficiently mitigating congestions, we investigate the
associated path computation problem aiming at maximizing the amount of traffic
that can be rerouted as well as the resilience against any 1-link failure. In
particular, we focus on two variants of this problem. First, we maximize the
residual flow after all possible failures. We show that the problem is NP-Hard,
and we solve it via a Benders decomposition algorithm. Then, to provide a
practical and scalable solution, we solve a relaxed variant problem, that
maximizes, instead of flow, the number of surviving alternative paths after all
possible failures. We provide a polynomial algorithm. Through numerical
experiments, we compare the two variants and show that they allow to increase
the amount of rerouted traffic and the resiliency of the network after any
1-link failure.
