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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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 HIGH-IMPACT PAPER 

Wavelength Converters Placement in Optical Networks Using Bee Colony Optimization

MARKOVIC, G. Z. See more information about MARKOVIC, G. Z. on SCOPUS See more information about MARKOVIC, G. Z. on IEEExplore See more information about MARKOVIC, G. Z. on Web of Science
 
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Download PDF pdficon (1,207 KB) | Citation | Downloads: 1,488 | Views: 3,776

Author keywords
artificial intelligence, computational complexity, optical fiber networks, wavelength converters, wavelength division multiplexing

References keywords
wavelength(26), networks(22), optical(19), placement(14), converter(11), communications(9), converters(7), algorithm(7), optimal(6), optimization(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-02-28
Volume 16, Issue 1, Year 2016, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.01001
Web of Science Accession Number: 000376995400001
SCOPUS ID: 84960106375

Abstract
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Full text preview
Wavelength converters placement (WCP) in all-optical WDM networks belongs to the class of hard combinatorial optimization problems. So far, this problem has been solved by various heuristic strategies or by application of metaheuristic approaches such as genetic algorithms (GA), particle swarm optimization (PSO), differential evolution (DE), etc. In this paper, we introduce the application of Bee Colony Optimization (BCO) metaheuristic to solve the WCP problem in all-optical WDM networks. Numerous studies prove that BCO is a fast, robust and computationally efficient tool in tackling complex optimization problems. The objective of the proposed BCO-WCP algorithm is to find the best placement of limited number of wavelength converters in given optical network such that the overall network blocking probability is minimized. To evaluate the performances of the BCO-WCP algorithm, numerous simulation experiments have been performed over some realistic optical network examples. The blocking probability performance and computational complexity are compared with optimal solution obtained by exhaustive search (ES) approach as well as with DE and PSO metaheuristics. It will be shown that the BCO-WCP algorithm is not only be able to produce high quality (optimal) solution, but significantly outperforms the computational efficiency of other considered approaches.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

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Cited-By CrossRef

[1] A metaheuristic approach for source traffic grooming in elastic optical networks, Miladić‐Tešić, Suzana, Marković, Goran, Nonković, Nikola, Radojičić, Valentina, Transactions on Emerging Telecommunications Technologies, ISSN 2161-3915, Issue 1, Volume 32, 2021.
Digital Object Identifier: 10.1002/ett.4097
[CrossRef]

[2] A Decision Support Model for Transportation Companies to Examine Driver Behavior, Čubranić-Dobrodolac, Marjana, Švadlenka, Libor, Marković, Goran Z., Dobrodolac, Momčilo, IEEE Transactions on Engineering Management, ISSN 0018-9391, Issue 10, Volume 70, 2023.
Digital Object Identifier: 10.1109/TEM.2021.3102879
[CrossRef]

[3] Optical splitter design for telecommunication access networks with triple-play services, Agalliu, Rajdi, Burtscher, Catalina, Lucki, Michal, Seyringer, Dana, Journal of Electrical Engineering, ISSN 1339-309X, Issue 1, Volume 69, 2018.
Digital Object Identifier: 10.1515/jee-2018-0004
[CrossRef]

[4] Energy-efficient clustering method for wireless sensor networks using modified gravitational search algorithm, Ebrahimi Mood, Sepehr, Javidi, Mohammad Masoud, Evolving Systems, ISSN 1868-6478, Issue 4, Volume 11, 2020.
Digital Object Identifier: 10.1007/s12530-019-09264-x
[CrossRef]

[5] A bee colony optimization (BCO) and type-2 fuzzy approach to measuring the impact of speed perception on motor vehicle crash involvement, Čubranić-Dobrodolac, Marjana, Švadlenka, Libor, Čičević, Svetlana, Trifunović, Aleksandar, Dobrodolac, Momčilo, Soft Computing, ISSN 1432-7643, Issue 9, Volume 26, 2022.
Digital Object Identifier: 10.1007/s00500-021-06516-4
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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