A Genetic Algorithm Based Approach for Static Virtual Topology Design in Optical Networks

Saha, Mounita; Sengupta, Indranil

doi:10.1109/indcon.2005.1590197

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…However, exact methods are not scalable; therefore, heuristic (Ramaswami et al, 1996;Dutta and Rouskas, 2000;Leonardi et al, 2000Leonardi et al, , 2005 and metaheuristic techniques (Mukherjee et al, 1996;Le et al, 2005;Saha and Sengupta, 2005) have been also proposed.…”

Section: Traditional Rwamentioning

confidence: 99%

Multiobjective Optimization in Optical Networks

Barán

Pinto-Roa

2015

Bio-Inspired Computation in Telecommunications

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Section: Traditional Rwamentioning

confidence: 99%

Multiobjective Optimization in Optical Networks

Barán

Pinto-Roa

2015

Bio-Inspired Computation in Telecommunications

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“…Although, there are a few studies on VT mapping [7] and design [8] using EAs, none of them considered survivability, except [9]. Ergin et al [9] proposed the only EA based approach for survivable VT mapping problem.…”

Section: B Related Literaturementioning

confidence: 99%

Performance Analysis of Nature Inspired Heuristics for Survivable Virtual Topology Mapping

Ergin

Kaldirim

Yayimli

et al. 2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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The high capacity of fibers used in optical networks, can be divided into many channels, using the WDM technology. Any damage to a fiber causes all the channels routed through this link to be broken, which may result in a serious amount of data loss. As a solution to this problem, the virtual layer can be mapped onto the physical topology, such that, a failure on any physical link does not disconnect the virtual topology. This is known as the survivable virtual topology mapping problem. In this study, we investigated the performance of two popular nature inspired heuristics, namely, evolutionary algorithms and ant colony optimization, in finding a survivable mapping of a given virtual topology while minimizing the resource usage. Our results show that both nature inspired heuristics perform remarkably well for this problem. Furthermore, both methods can obtain high quality solutions in less than a minute.

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“…[5] studied the problem using a local search algorithm, while Kurant and Thiran [6] used an algorithm that divides the survivable mapping problem into subproblems. There are a few studies on VT mapping [7] and design [8] using EAs, however, survivability is not considered in any of them except [9]. Ergin et.…”

Section: B Related Literaturementioning

confidence: 99%

Ant colony optimization for survivable virtual topology mapping in optical WDM networks

Kaldirim

Ergin

Uyar

et al. 2009

2009 24th International Symposium on Computer and Information Sciences

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The high capacity of fibers used in optical networks, can be divided into many channels, using the WDM technology. Any damage to a fiber causes all the channels routed through this link to be broken, which may result in a serious amount of data loss. As a solution to this problem, the virtual layer can be mapped onto the physical topology, such that, a failure on any physical link does not disconnect the virtual topology. This is known as the survivable virtual topology mapping problem. In this study, our aim is to determine a suitable ant colony optimization algorithm to solve this problem. Our results show that ant colony heuristics perform remarkably well while producing high quality solutions in less than half a minute.

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A Genetic Algorithm Based Approach for Static Virtual Topology Design in Optical Networks

Cited by 14 publications

References 9 publications

Multiobjective Optimization in Optical Networks

Multiobjective Optimization in Optical Networks

Performance Analysis of Nature Inspired Heuristics for Survivable Virtual Topology Mapping

Ant colony optimization for survivable virtual topology mapping in optical WDM networks

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