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

  • @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).