Tabu search optimization in translucent network regenerator allocation

Pan, Zhiyan; Châtelain, B.; Plant, David V.; Gagnon, François; Tremblay, Christine; Bernier, Éric

doi:10.1109/broadnets.2008.4769153

Cited by 7 publications

(5 citation statements)

References 12 publications

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“…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%

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%

Optimal regenerator placement in translucent optical networks

Rahman

Bandyopadhyay

Aneja

2015

Optical Switching and Networking

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“…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 [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. In [9], the authors present an exhaustive search algorithm that minimizes the number of regenerators, or regenerator sites.…”

Section: Reviewmentioning

confidence: 99%

“…Two main problems have been investigated in the literature for such networks. The first is the regenerator placement (RP) problem [5][6][7][8], where the goal is to determine the minimum number of regenerators (alternatively, the minimum number of regeneration sites [9,10]) and their locations that needs to be deployed in order to support a specified set of lightpath demands. The second is the routing with regenerator assignment (RRA) problem [11,12], where, the number and the locations of the regenerators are already known, and the goal is to use the available regenerators and other resources as efficiently as possible, when performing the RWA for each lightpath.…”

Section: Introductionmentioning

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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“…As examples, (i) in [24], the authors focused on the planning and deployment of re-amplification, re-shaping, and re-timing (3R) regenerators accordingly to the network and traffic information; (ii) in [25], two heuristics were proposed for the regenerator assignment. In this case, one of the heuristics targets to deploy the highest order modulation format possible, while the other one tries to reach the maximum transmission distance before performing signal regeneration; (iii) in [26], three metrics were proposed for the regenerator placement focusing on minimizing the network cost, which was evaluated as a function of the total number of regenerators and nodes with 3R capacity; (iv) in [27], the authors focused on minimizing the total number of regenerators when network protection capability was also deployed. (v) in [28] an optimized regenerator assignment strategy based on the QoT of the links was reported.…”

mentioning

confidence: 99%

Transparent vs Translucent Multi-Band Optical Networking: Capacity and Energy Analyses

Sadeghi

Correia

Souza³

et al. 2022

J. Lightwave Technol.

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Multi-band optical fiber transmission is generally proposed for capacity upgrades in optical transport networks. To comprehensively assess the potential of multi-band transmission, key metrics such as the potential capacity increase, energy consumption, and the number of required interfaces must be evaluated for different transmission scenarios. We consider progressive spectral exploitation, starting from the C-band only and up to C+L+S+U-band transmission, for both transparent and translucent solutions that exploit optical signal regeneration. By considering accurate state-of-the-art physical layer models, we derive a networking performance metric that enables the comparison of different solutions in terms of capacity allocation and energy consumption. For a translucent network design, different regenerator placement algorithms are compared, with the aim of minimizing energy consumption. The proposed network-wide numerical analysis shows that, for spectral occupations exceeding the C+L-band, translucent solutions can significantly increase network capacity, while leading to a similar energy consumption per transmitted bit as in the transparent design case, but they require the deployment of additional line interfaces. Significantly, these results provide evidence that the transparent exploitation of an additional transmission band produces a capacity increment that is at least comparable to that of a translucent solution based on already-in-use bands. Since this is attained at the expense of fewer line interfaces, it is a key finding suggesting that extending the number of bands supported is a cost-effective approach to scaling the capacity of existing fiber infrastructures.

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Tabu search optimization in translucent network regenerator allocation

Cited by 7 publications

References 12 publications

Optimal regenerator placement in translucent optical networks

Optimal regenerator placement in translucent optical networks

Optimal regenerator assignment and resource allocation strategies for translucent optical networks

Transparent vs Translucent Multi-Band Optical Networking: Capacity and Energy Analyses

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