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Software-Defined Networking Approaches for Link Failure Recovery: A Survey

Author

Listed:
  • Jehad Ali

    (Department of Computer Engineering, Ajou University, Suwon 16499, Korea)

  • Gyu-min Lee

    (Department of Computer Engineering, Ajou University, Suwon 16499, Korea)

  • Byeong-hee Roh

    (Department of Computer Engineering, Ajou University, Suwon 16499, Korea)

  • Dong Kuk Ryu

    (Agency for Defense Development, Seoul 05771, Korea)

  • Gyudong Park

    (Agency for Defense Development, Seoul 05771, Korea)

Abstract

Deployment of new optimized routing rules on routers are challenging, owing to the tight coupling of the data and control planes and a lack of global topological information. Due to the distributed nature of the traditional classical internet protocol networks, the routing rules and policies are disseminated in a decentralized manner, which causes looping issues during link failure. Software-defined networking (SDN) provides programmability to the network from a central point. Consequently, the nodes or data plane devices in SDN only forward packets and the complexity of the control plane is handed over to the controller. Therefore, the controller installs the rules and policies from a central location. Due to the central control, link failure identification and restoration becomes pliable because the controller has information about the global network topology. Similarly, new optimized rules for link recovery can be deployed from the central point. Herein, we review several schemes for link failure recovery by leveraging SDN while delineating the cons of traditional networking. We also investigate the open research questions posed due to the SDN architecture. This paper also analyzes the proactive and reactive schemes in SDN using the OpenDayLight controller and Mininet, with the simulation of application scenarios from the tactical and data center networks.

Suggested Citation

  • Jehad Ali & Gyu-min Lee & Byeong-hee Roh & Dong Kuk Ryu & Gyudong Park, 2020. "Software-Defined Networking Approaches for Link Failure Recovery: A Survey," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4255-:d:361650
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    Cited by:

    1. Rashid Amin & Muzammal Majeed & Farrukh Shoukat Ali & Adeel Ahmed & Mudassar Hussain, 2022. "Reliability Awareness Multiple Path Installation in Software Defined Networking using Machine Learning Algorithm," International Journal of Innovations in Science & Technology, 50sea, vol. 4(5), pages 158-172, July.

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