Optimal Routing Path Calculation for SDN using Genetic Algorithm

AUTHORS

Man Soo Han,Dept. Information and Communications, Mokpo National Univ., Republic of Korea

ABSTRACT

Path computation element (PCE) is a network entity that makes a calculation for the best routing path between a source node and a destination node in networks. It is a key technology to support virtualization of software defined network (SDN) and network function virtualization (NFV) for which packet processing power of virtual network nodes as well as bandwidth between them should be considered as a major parameter for the routing path calculation. However, current analytic algorithms including Dijkstra widely used can’t be applicable to some critical cases due to non-linear characteristic of parameters in which both link and performance costs are considered as parameters. This paper addresses that the current shortest path first algorithms are limited to a linear metric, and proposes a new genetic algorithm (GA) to support a non-linear metric for both link and performance costs.

 

KEYWORDS

PCE, genetic algorithm, shortest path, SDN

REFERENCES

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CITATION

  • APA:
    Han, M. S. (2018). Optimal Routing Path Calculation for SDN using Genetic Algorithm. International Journal of Hybrid Information Technology, 11(3), 7-12. 10.21742/IJHIT.2018.11.3.02
  • Harvard:
    Han, M. S. (2018). "Optimal Routing Path Calculation for SDN using Genetic Algorithm". International Journal of Hybrid Information Technology, 11(3), pp.7-12. doi:10.21742/IJHIT.2018.11.3.02
  • IEEE:
    [1] M. S. Han, "Optimal Routing Path Calculation for SDN using Genetic Algorithm". International Journal of Hybrid Information Technology, vol.11, no.3, pp.7-12, Sep. 2018
  • MLA:
    Han Man Soo. "Optimal Routing Path Calculation for SDN using Genetic Algorithm". International Journal of Hybrid Information Technology, vol.11, no.3, Sep. 2018, pp.7-12, doi:10.21742/IJHIT.2018.11.3.02
 

COPYRIGHT

Creative Commons License
© 2018 Han Man Soo. Published by Global Vision Press. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CCBY4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ISSUE INFO

  • Volume 11, No. 3, 2018
  • ISSN(p):1738-9968
  • ISSN(e):2652-2233
  • Published:Sep. 2018

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