Wind Driven Based Heuristic Solution for Multiobjective Traffic Grooming in Optical Networks

One of the major problem faced by the optical networks is traffic grooming. The large size of data and the speedy transmission leads to traffic grooming. In this research paper, the wind driven optimization (WDO) technique has been used for optimizing the traffic grooming in the optical network. The...

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Veröffentlicht in:Wireless personal communications Jg. 110; H. 3; S. 1475 - 1491
Hauptverfasser: Kaur, Harpreet, Rattan, Munish
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.02.2020
Springer Nature B.V
Schlagworte:
Algorithms
Communications Engineering
Computer Communication Networks
Computer networks
Engineering
Evolutionary algorithms
Evolutionary computation
Multiple objective analysis
Networks
Optical communication
Optimization
Parameters
Route planning
Scientific papers
Shortest-path problems
Signal,Image and Speech Processing
Traffic speed
Wave division multiplexing
Wavelength division multiplexing
Setcoverage
Wavelength division multiplexing
Grooming
Multi-objective
Wind driven optimization
Hypervolume
ISSN:0929-6212, 1572-834X
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Zusammenfassung:One of the major problem faced by the optical networks is traffic grooming. The large size of data and the speedy transmission leads to traffic grooming. In this research paper, the wind driven optimization (WDO) technique has been used for optimizing the traffic grooming in the optical network. The paper describes the model of optical systems, WDM concepts, optimization and its components. Then, the issue of traffic grooming is discoursed in paper that includes information on its types, parameters, objective function, variables, and related constraints. The results achieved with the implementation of WDO algorithm proved to be cost effective. Two multiobjective indicators are used in the study. Results have been compared with multiobjective evolution algorithm based on decomposition (MOEA/D) and DEPT, i.e., differential evolution with Pareto tournaments in terms of multi-objective indicator hypervolume. Hypervolume is the effective quantative parameter that calculate the proximity of the calculated solution to the true pareto front. Multiobjective indicator set coverage values have also been evaluated using WDO and are compared with the setcoverage values obtained with the use of shortest path routing and first fit wavelength algorithm. Results obtained were quite promising in terms of hypervolume and setcoverage values both. Thus, WDO algorithm can be stated as optimizer as compared to existing techniques DEPT, MOEA/D and shortest path routing and first fit wavelength assignment method.
Bibliographie:ObjectType-Article-1
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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-019-06796-y