Abstract
Traffic grooming is important in the design and operation of translucent
optical networks. This paper investigates sub-wavelength traffic grooming
in a translucent optical network and shows how to take advantage of sub-wavelength
traffic grooming capability of sparsely distributed opaque switch nodes. An
efficient heuristic, called the virtual nodal degree ranked algorithm, is
employed to select the best locations for opaque switch nodes. New mixed-integer
linear programming (MILP) optimization models are developed to optimally groom
sub-wavelength traffic demand in the translucent optical network. The models
maximize served sub-wavelength traffic demand under a limited network capacity
and minimize required wavelength capacity subject to the condition that all
the traffic demands are served. The models are novel in optimization methodology
because they incorporate both the arc-node and
the arc-path multi-commodity
optimization techniques for a single problem. Based on simulation studies,
it is found that the performance of sub-wavelength traffic grooming of a translucent
network is substantially improved by increasing the number of opaque switch
nodes. For some network topologies, the performance saturates as the number
of opaque switch nodes increases, though the phenomenon is not general for
any type of network topology.
© 2009 IEEE
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