Dense wavelength division multiplexing
(DWDM) transport networks are evolving to support dy-
namic setup/teardown of wavelength services. This is be-
coming possible mainly via node architectures with
flexible add/drop port utilization, where an already de-
ployed transponder can be tuned to any wavelength and
configured to transmit/receive via any output/input direc-
tion, and advanced control and management software,
which provide the means to remotely reconfigure equip-
ment end to end. In long-haul networks, exploiting these
capabilities to quickly set up new services also demands
that 3R regenerators (performing reamplification, reshap-
ing, and retiming) have been deployed in advance. This pa-
per proposes a framework that, first, characterizes
stochastically the fitness of each network node as a place-
holder for predeployed regenerators based on the network
and traffic information available and, second, distributes
the set of regenerators to match as closely as possible the
fitness values. Network simulation on a reference long-haul
network under dynamic traffic is used to evaluate the effec-
tiveness of four fitness estimation strategies, each based on
a different set of forecasts about the expected network op-
erating conditions. The results highlight that when the
main assumptions embedded in these strategies hold dur-
ing network operation significant benefits can be attained,
in terms of lower service blocking probability and/or re-
duced number of predeployed 3R regenerators, by exploit-
ing additional information when computing the node ’ s
fitness values.