A genetic algorithm for traffic grooming in unidirectional SONET/WDM rings

Mukhopadhyay, Mainaak; Biswas, Utpal; Naskar, Mrinal Kanti

doi:10.1109/indico.2004.1497750

Cited by 10 publications

(12 citation statements)

References 4 publications

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“…Its applications include diverse areas such as job-shop scheduling, training neural nets, image feature extraction or recognition, pattern recognition, data mining, bio-informatics etc. Genetic algorithms [26][27][28][29] are modeled on the concept of natural selection and evolution as in the same way the species adopt their environment. GAs are not random search algorithms rather the search is done in a directed manner inside the solution space exploiting the advantages of natural genetic system.…”

Section: Proposed Algorithmmentioning

confidence: 99%

Genetic evolutionary algorithm for optimal allocation of wavelength converters in WDM optical networks

Roy

Naskar

2008

Photon Netw Commun

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In this article, a genetic evolutionary algorithm is proposed for efficient allocation of wavelength converters in WDM optical networks. Since wavelength converters are expensive, it is desirable that each node in WDM optical networks uses a minimum number of wavelength converters to achieve a near-ideal performance. The searching capability of genetic evolutionary algorithm has been exploited for this purpose. The distinguished feature of the proposed approach lies in handling the conflicting circumstances during allocation of wavelength converters considering various practical aspects (e.g., spatial problem, connectivity of a node with other nodes) rather than arbitrarily to possibly improve the overall blocking performance of WDM optical networks. The proposed algorithm is compared with a previous approach to establish its effectiveness and the results demonstrate the ability of the proposed algorithm to efficiently solve the problem of Optimal Wavelength Converters Allocation (OWCA) in practical WDM optical networks.

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Section: Proposed Algorithmmentioning

confidence: 99%

Genetic evolutionary algorithm for optimal allocation of wavelength converters in WDM optical networks

Roy

Naskar

2008

Photon Netw Commun

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“…The resulting networks are called WDM traffic grooming networks. The ratio of N to the smallest value of M is called the grooming ratio [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…Thus careful grooming of low-speed traffic can reduce the electronic multiplexing cost. Most of the related works have focussed on minimizing the number of SADMs in SONET/WDM rings [5,6,[8][9][10][11], which is proven to be NP-complete [10]. However, the total cost of an optical network not only depends on the cost of SADMs but also on the cost of wavelengths and the grooming ratio.…”

Section: Introductionmentioning

confidence: 99%

“…Biologically inspired operators like selection, crossover, and mutation are used over a number of generations for generating potentially better strings. A GA-based minimization of SADMs in unidirectional rings has been proposed in [5]. In this article, the problem of minimization of cost of a SONET/WDM unidirectional ring has been modeled as a multiobjective optimization (MOO) problem [18][19][20][21][22][23] which simultaneously minimizes the number of SADMs, the number of wavelengths, and the grooming ratio.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective evolutionary approach to cost-effective traffic grooming in unidirectional SONET/WDM rings

et al. 2008

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Traffic grooming in optical networks is the process of multiplexing and demultiplexing low-speed traffic streams onto high-speed wavelengths. The research in the domain of traffic grooming mainly focuses on minimizing number of SONET add/drop multiplexers (SADMs) in SONET/WDM rings and it has been shown that they can potentially be reduced by careful assignment of low-speed traffic streams onto high-speed wavelengths. However, the cost of the network not only depends on the number of SADMs, but also the number of wavelengths and the grooming ratio. It is often the case that all of them cannot be minimized simultaneously. In this article, the problem of minimization of cost of a SONET/WDM unidirectional ring has been modeled as a multiobjective optimization problem which simultaneously minimizes the number of SADMs, the number of wavelengths, and the grooming ratio. A popular multiobjective genetic algorithm (NSGA-II) has been used as the underlying optimization tool. The resultant set of nearPareto-optimal solutions contains a number of nondominated solutions, which the user can judge relatively and pick up the most promising one according to the problem requirements.Performance of the proposed algorithm has been demonstrated on different network topologies.

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“…As there are some constraints (e.g., power consumption) in increasing the number of wavelength channels without limit using WDM technology, the recent trend is to employ TDM slots within a wavelength channel itself. The resulting network configuration is known as WDM-TDM network or WDM grooming network [8][9][10].…”

mentioning

confidence: 99%

Simulation-based SONET ADM optimization approach for dynamic traffic grooming in WDM optical networks

Roy

Naskar

2008

Photon Netw Commun

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The article addresses a simulation-based optimization approach for allocation of ADMs in WDM optical networks with stochastic dynamic traffic. Since ADMs are expensive, it is desirable that if each node in WDM optical networks can use a minimum number of ADMs to achieve a near-ideal performance. In this article, first, the utilization statistics of ADMs are gathered by simulation. Then, ADMs are allocated based on the utilization statistics. In this respect, a simple sorting mechanism is used. The distinguished feature of the proposed approach is that it shows the way to allocate ADMs at the nodes of WDM optical networks with stochastic dynamic traffic. The experimental results ensure that the proposed approach can solve the problem of allocating ADMs in practical WDM optical networks considering stochastic dynamic traffic.

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A genetic algorithm for traffic grooming in unidirectional SONET/WDM rings

Cited by 10 publications

References 4 publications

Genetic evolutionary algorithm for optimal allocation of wavelength converters in WDM optical networks

Genetic evolutionary algorithm for optimal allocation of wavelength converters in WDM optical networks

Multiobjective evolutionary approach to cost-effective traffic grooming in unidirectional SONET/WDM rings

Simulation-based SONET ADM optimization approach for dynamic traffic grooming in WDM optical networks

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