Non-Cooperative Design of Translucent Networks

Châtelain, B.; Mannor, Shie; Gagnon, François; Plant, David V.

doi:10.1109/glocom.2007.447

Cited by 9 publications

(13 citation statements)

References 16 publications

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“…A game theoretic approach to RPP was proposed in [63]. Using optical reach to estimate impairments, an ILP for an optimal solution and a heuristic, based on game theoretic approach, were proposed in [22] for a network using path protection. Tabu Search was used in [64].…”

Section: Algorithms For Rpp In Network Handling Ad-hoc Lightpath Demmentioning

confidence: 99%

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Optimal regenerator placement in translucent optical networks

Rahman

Bandyopadhyay

Aneja

2015

Optical Switching and Networking

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Section: Algorithms For Rpp In Network Handling Ad-hoc Lightpath Demmentioning

confidence: 99%

“…This requires a minimum of 2 regenerator nodes and one solution is to select nodes B and D to be regenerator nodes. The RPP problem is known to be NP-complete [14,20,21] and heuristics are typically used to solve this problem [3,14,[20][21][22][23][24][25][26] for relatively larger networks.…”

Section: Introductionmentioning

confidence: 99%

Optimal regenerator placement in translucent optical networks

Rahman

Bandyopadhyay

Aneja

2015

Optical Switching and Networking

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“…Constraint (12) adds the distance of link i → j, if it is on the physical route for lightpath p, to the value of δ p i, j , which represents the distance of the previous node i, from the beginning of the segment. Finally, (13) ensures that the distance from the beginning of a segment to any node j in the given segment (and hence the maximum segment length), never exceeds r max . (f) Constraint (14) puts an upper limit on the number of regenerations that a single lightpath can undergo.…”

Section: Justification Of the Ilp Equationsmentioning

confidence: 99%

“…As mentioned earlier, two main problems that have been studied in the literature, for wide-area translucent network design, are the RP problem and the RRA problem. A number of ILP-based approaches [6,7,10,13], for the sparse RP problem have been proposed in recent years, where the goal of each is, typically, to minimize regenerator usage. In [6], the authors propose an ILP formulation, where the objective is to maximize the number of lightpaths that can be established.…”

Section: Reviewmentioning

confidence: 99%

“…In [7], the authors present a hybrid ILP for the RP problem, which also considers physical layer impairments. In [13], an ILP and a game theoretic algorithm for minimizing the number of regenerators is proposed. The ILP formulation in [10] minimizes the number of regeneration sites, but only finds appropriate routes for the lightpaths, and does not consider wavelength assignment.…”

Section: Reviewmentioning

confidence: 99%

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Optimal regenerator assignment and resource allocation strategies for translucent optical networks

2011

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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 benchbe developed in 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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