Abstract
With increasing demands for dynamic high data-rate
private line services from large customers, network
carriers have begun to provide flexible on-demand
connections to construct these customers' networks.
Advances in optical devices have greatly improved the
reconfigurability of the optical layer, which makes it
possible to provide optical on-demand services at
wavelength granularity (10 Gbps to 40 Gbps per channel).
This new dynamic
wavelength service model allows a
customer owning or leasing a few terminal ports in the
network to connect these ports on demand.The network must be pre-dimensioned with enough
resources to support any possible connection
configuration between the preallocated ports of a
dynamic wavelength customer. In this paper, we introduce
a resource optimization problem for dynamic wavelength
services and propose a few efficient techniques to
tackle this challenging problem. A heuristic optimizer
based on a combination of simulated annealing and
genetic algorithms is developed to solve the problem
efficiently for large networks. We show that our solver
can produce optimization solutions within 7% overhead of
a lower bound with a small amount of computation.
© 2011 IEEE
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