Optimal regenerator assignment and resource allocation strategies for translucent optical networks |
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Authors: | Ying Chen Ataul Bari Arunita Jaekel |
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Affiliation: | (1) Athens Information Technology, 19.5 Km Markopoulo Avenue, 19002 Peania, Attiki, Greece;(2) Department of Electrical and Computer Engineering, University of Cyprus, 1678 Nicosia, Cyprus;(3) Department of Engineering Science and Physics, College of Staten Island/The City University of New York, Staten Island, NY 10314, USA |
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Abstract: | Physical layer impairments in wavelength-routed networks limit the maximum distance, a signal can travel in the optical domain,
without significant distortion. Therefore, signal regeneration is required at some intermediate nodes for long-haul lightpaths.
In translucent WDM networks, sparsely located regenerators at certain nodes can be used to offset the impact of physical layer
impairments. The routing and wavelength assignment (RWA) techniques in such translucent networks need to take into consideration
the availability of regenerators and the maximum optical reach of the transparent lightpaths (without any regeneration). Although
there has been significant research interest in RWA algorithms for translucent networks, much of the research has focused
on dynamic RWA techniques. Only a handful of recent papers have considered the static (offline) case, and they typically propose heuristic algorithms to solve this complex design problem for practical networks.
In this paper, we propose a generalized integer linear program (ILP) based formulation for static regenerator assignment and RWA in translucent WDM optical networks, with sparse regenerator placement. To the best of our
knowledge, such a formulation that optimally allocates resources for a set of lightpaths for translucent networks, given the
physical network, the locations of the regenerators, and the maximum optical reach has not been considered before. The proposed
formulation is important for two reasons. First, it can serve as a benchmark for evaluating different heuristic approaches
that may be developedin the future. Second, we show that using a novel node representation technique, it is possible to drastically
reduce the number of integer variables. This means that unlike existing ILP formulations, our approach can actually be used
to generate optimal solutions for practical networks, with hundreds of lightpath demands. |
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