Dragonfly addressing model for software defined networks based on datacenters

  • Authors

    • Heba Hassan Benha Faculty of Engineering
    • Amr Al-Awamry Benha Faculty of Engineering
    • Mohammed Abdelhalim College of Computing and Information Technology, Arab Academy for Science, Technology & Maritime Transport
    2018-04-30
    https://doi.org/10.14419/ijet.v7i2.9769
  • Software Defined Networking, Network Functions Virtualization, Dragonfly topology, Fat Tree topology.

  • Abstract

    With the advancement of technology, virtualization has become very important for Information Technology (IT) experts. Network Functions Virtualization (NFV) means to address issues resulting from complex hardware-based appliances by developing standard IT virtualization technologies. Software Defined Networking (SDN) solidifies the advantages of datacenter virtualization, increases resource flexibility and utilization, and reduces infrastructure costs and overhead. Datacenter networks should have the ability to guarantee high throughput and resiliency. For such reasons, typical datacenter networks (e.g. Fat Tree) have been evolved to high-radix networks (e.g. Dragonfly). This work aims to investigate how SDN and NFV can improve the advantages of datacenter virtualization by utilizing datacenter topologies such as Dragonfly (DF) topology and Fat Tree (FT) topology in SDN, thus expanding resource flexibility and utilization and diminishing infrastructure costs and overhead. By using Dragonfly topology, the cost is reduced and better scalability is introduced compared to the folded clos networks such as Fat Tree. Here in, a novel addressing scheme is proposed for Dragonfly topology with simulation results included utilizing Mininet, which incorporates MiniEdit that is used to create and run network simulations.

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  • How to Cite

    Hassan, H., Al-Awamry, A., & Abdelhalim, M. (2018). Dragonfly addressing model for software defined networks based on datacenters. International Journal of Engineering & Technology, 7(2), 657-662. https://doi.org/10.14419/ijet.v7i2.9769

    Received date: 2018-03-03

    Accepted date: 2018-04-27

    Published date: 2018-04-30