A Distributed Memetic Algorithm for the Routing and Wavelength Assignment Problem

Fischer, Thomas; Bauer, Kerstin; Merz, Peter

doi:10.1007/978-3-540-87700-4_87

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…A distributed memetic algorithm (similar to genetic algorithm) for static routing and wavelength assignment problem by introducing a recombination operator and a scheme for distributing the computation is provided in [28]. They focus on minimizing the number of used wavelengths to establish the given requests under different recombination rates.…”

Section: Existing Workmentioning

confidence: 99%

Distributed dynamic grooming routing and wavelength assignment in WDM optical mesh networks

Jain

Pal

2010

Photon Netw Commun

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The bandwidth of a wavelength channel in WDM optical networks is very high compared to the user's requirements for various applications. Therefore, there is a scope for better utilization of channel bandwidth by traffic grooming, in which several user's channels are multiplexed for transmission over a single channel. Several research works have been reported on traffic grooming routing and wavelength assignment (GRWA) for static and dynamic traffic pattern under centralized environment. Distributed dynamic grooming routing and wavelength assignment (DDGRWA) is a new and quite unexplored area in WDM optical mesh networks. This article introduces the concept of distributed traffic grooming in WDM mesh networks which also includes virtual topology construction, reconfiguration, routing and wavelength assignment in the distributed environment assuming incoming traffic to be dynamic in nature. We have also presented simulation results of our algorithm on dynamically generated traffic under various network topologies.

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Section: Existing Workmentioning

confidence: 99%

Distributed dynamic grooming routing and wavelength assignment in WDM optical mesh networks

Jain

Pal

2010

Photon Netw Commun

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Memetic Algorithms

Moscato

Berretta

Cotta

2011

Wiley Encyclopedia of Operations Research and Management Science

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Memetic algorithms (MAs) are population‐based search strategies that have been extensively used as metaheuristics for optimization problems in a large number of domains. They are based on the synergistic combination of different algorithmic solvers, with an emphasis on hybridizations with advanced mathematical programming techniques. The synergies are obtained by balancing competitive and cooperative interactions among software agents, which are allowed to have different search strategies and sporadically interact. The paradigm was specially designed for heterogeneous distributed systems and parallel computers 20 years ago. We present a brief historical perspective on MAs, an outline of their algorithmic structural template, and some relevant design aspects of these techniques. The strong momentum of the field is further illustrated by an overview of up‐to‐date algorithmic developments of the paradigm and by highlighting some of the most recent applications published in the literature.

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A Distributed Memetic Algorithm for the Routing and Wavelength Assignment Problem

Cited by 2 publications

References 14 publications

Distributed dynamic grooming routing and wavelength assignment in WDM optical mesh networks

Distributed dynamic grooming routing and wavelength assignment in WDM optical mesh networks

Memetic Algorithms

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