A Pro-Active and Adaptive Mechanism for Fast Failure Recovery in SDN Data Centers

  • Renuga KanagaveluEmail author
  • Yongqing Zhu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 886)


As modern data centers continue to grow in size and complexity to host different kinds of applications, it is required to have an efficient proactive failure management for Data Center reliability. Although Software-Defined Networking (SDN) and its implementation OpenFlow facilitate dynamic management and the configuration of Data center networks, network failure recovery in a timely manner remains great challenging. The centralized SDN controller is responsible for monitoring the entire network health status and maintain the end-to-end connectivity between the hosts. In the event of a link failure, the controller either computes a new backup path reactively on demand and creates flow table entries for the new backup path, or pro-actively computes the backup path a-priori and set up flow table rules for the pre-defined backup path. Switching to the predefined backup path locally results in faster recovery time compared to switching to the backup path that establish on demand. In this paper, we propose a proactive mechanism to provide fast recovery upon a link failure. With the proposed proactive approach, we compute the recovery (or backup) paths for the flows prior to failures and install appropriate rules in the forwarding tables at the switches in advance. Such recovery paths are adaptively updated based on the current load state of the network to improve resource efficiency and reduce congestion. By providing the backup forwarding rules in advance, upon a failure, the failed traffic is rerouted without interacting with the controller, thus ensuring fast recovery. We demonstrate the effectiveness of the proposed mechanisms using an experimental testbed with Openstack platform and simulated environment with Mininet.


Software-defined network Fast-failover OpenFlow Recovery Data center network 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Data Center Technology DivisionA*STAR Data Storage InstituteSingaporeSingapore

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