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Testbeds and Research Infrastructures for the Development of Networks and Communications. 14th EAI International Conference, TridentCom 2019, Changsha, China, December 7-8, 2019, Proceedings

Research Article

Genetic Algorithm Based Solution for Large-Scale Topology Mapping

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  • @INPROCEEDINGS{10.1007/978-3-030-43215-7_5,
        author={Nada Osman and Mustafa ElNainay and Moustafa Youssef},
        title={Genetic Algorithm Based Solution for Large-Scale Topology Mapping},
        proceedings={Testbeds and Research Infrastructures for the Development of Networks and Communications. 14th EAI International Conference, TridentCom 2019, Changsha, China, December 7-8, 2019, Proceedings},
        proceedings_a={TRIDENTCOM},
        year={2020},
        month={3},
        keywords={Network simulation Topology mapping Testbeds Genetic algorithm},
        doi={10.1007/978-3-030-43215-7_5}
    }
    
  • Nada Osman
    Mustafa ElNainay
    Moustafa Youssef
    Year: 2020
    Genetic Algorithm Based Solution for Large-Scale Topology Mapping
    TRIDENTCOM
    Springer
    DOI: 10.1007/978-3-030-43215-7_5
Nada Osman1,*, Mustafa ElNainay,*, Moustafa Youssef1,*
  • 1: Alexandria University
*Contact email: nada_s_osman@alexu.edu.eg, ymustafa@alexu.edu.eg, moustafa@alexu.edu.eg

Abstract

Simulating large-scale network experiments requires powerful physical resources. However, partitioning could be used to reduce the required power of the resources and to reduce the simulation time. Topology mapping is a partitioning technique that maps the simulated nodes to different physical nodes based on a set of conditions. In this paper, genetic algorithm-based mapping is proposed to solve the topology mapping problem. The obtained results prove a high reduction in simulation time, in addition to high utilization of the used resources (The number of used resources is minimum).

Keywords
Network simulation Topology mapping Testbeds Genetic algorithm
Published
2020-03-05
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-43215-7_5
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