Link Failure Recovery in SDN: High Efficiency, Strong Scalability and Wide Applicability

Link failures are commonly observed in computer networks, including the newly emerging Software Defined Network (SDN). Considering that failure recovery methods used in traditional networks cannot be applied to SDN networks directly, we propose a method named pro-VLAN in this paper, which calculates a backup path and assigns a unique VLAN id for each link of the network based on the protection mechanism. It makes the most of SDN’s features and can recover a single link failure in SDN with the advantages of high efficiency, strong scalability and wide applicability. More specifically, high efficiency (i.e., a fast failure recovery with a low memory consumption) is achieved by calculating backup paths for each link instead of each flow and using group tables to switch backup paths automatically and locally when failures occur. Strong scalability (i.e., the amount of backup flow entries per switch is stable) is achieved by keeping the amount of links per switch no matter how the network scale extends or how ...

[1]  Alan L. Cox,et al.  Scalable Multi-Failure Fast Failover via Forwarding Table Compression , 2016, SOSR.

[2]  Jian Wang,et al.  A Fault Diagnosis Method Based on Active Example Selection , 2018, J. Circuits Syst. Comput..

[3]  Piet Demeester,et al.  Network Recovery: Protection and Restoration of Optical, SONET-SDH, IP, and MPLS , 2004 .

[4]  Nick Feamster,et al.  CORONET: Fault tolerance for Software Defined Networks , 2012, 2012 20th IEEE International Conference on Network Protocols (ICNP).

[5]  Marco Canini,et al.  Automatic failure recovery for software-defined networks , 2013, HotSDN '13.

[6]  Wei Zhang,et al.  Failure recovery using vlan-tag in SDN: High speed with low memory requirement , 2016, 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC).

[7]  Piero Castoldi,et al.  OpenFlow-based segment protection in Ethernet networks , 2013, IEEE/OSA Journal of Optical Communications and Networking.

[8]  Didier Colle,et al.  OpenFlow: Meeting carrier-grade recovery requirements , 2013, Comput. Commun..

[9]  W. Marsden.  I and J , 2012 .

[10]  Chen-Nee Chuah,et al.  Characterization of Failures in an Operational IP Backbone Network , 2008, IEEE/ACM Transactions on Networking.

[11]  Suresh Subramaniam,et al.  Survivability in optical networks , 2000, IEEE Netw..

[12]  Ying Zhang,et al.  Fast failover for control traffic in Software-defined Networks , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[13]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[14]  Michael J. Freedman,et al.  Ravana: controller fault-tolerance in software-defined networking , 2015, SOSR.

[15]  Thierry Turletti,et al.  A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks , 2014, IEEE Communications Surveys & Tutorials.

[16]  Fernando M. V. Ramos,et al.  Software-Defined Networking: A Comprehensive Survey , 2014, Proceedings of the IEEE.

[17]  Tongquan Wei,et al.  Fault-Tolerant Task Scheduling for Mixed-Criticality Real-Time Systems , 2017, J. Circuits Syst. Comput..

[18]  Min Zhu,et al.  B4: experience with a globally-deployed software defined wan , 2013, SIGCOMM.

[19]  Weifa Liang,et al.  Cost Minimization for Rule Caching in Software Defined Networking , 2016, IEEE Transactions on Parallel and Distributed Systems.

[20]  Marco Canini,et al.  FatTire: declarative fault tolerance for software-defined networks , 2013, HotSDN '13.

[21]  M. Suzuki,et al.  The IEEE P1520 standards initiative for programmable network interfaces , 1998 .

[22]  Qiang Wang,et al.  A Path-Counter Method for Fault-Tolerant Minimal Routing Algorithms in 2D Mesh , 2018, J. Circuits Syst. Comput..