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ECODE Usage of  IBBT Virtual Wall (iLab.t)
SRLG detection and identification from mining of link state protocol data Infer Shared Risk Group (SRLG) from Link state routing information (LSA) arrival pattern to prevent successive SPT re-computation upon shared-risk failure (affects multiple links simultaneously) Current Link-state routing Link-state Routing    Machine Learning 4 8 3 7 2 6 1 5 4 8 3 7 2 6 1 5 First SPT Recomputation LSA(1,2) 4 8 3 7 2 6 1 5 Second  SPT Recomputation LSA(7,8) LSA(7,8) Failure Failure 4 8 3 7 2 6 1 5 4 8 3 7 2 6 1 5 Single SPT Recomputation  taking into account both link failures LSA(1,2) LSA(7,8) Failure Failure SRG SRG SRG SRG time LSA(1,2) LSA(7,8) receive predict LSA link [1,2] and [7,8] share the same risk (belong to the same SRG)
Experimental Development OSPF  Routing engine RIB FEA FIB control forwarding Hello message and LSA Machine Learning Engine XORP e X tensible  O pen  R outer  P latform  Hello message and LSA OSPF OSPF IP IP LSA SRLG ,[object Object],[object Object],[object Object]
Experimental Setup ,[object Object],[object Object],emulated topology ,[object Object],[object Object],[object Object],[object Object],ctl vhost-0 vid Kvm virtual machines OSPF area video  output Demo control Video streaming
Demonstration – recovery times ,[object Object],[object Object],01/12/11
What did we learn ? ,[object Object],For failures of SRLG containing only non-adjacent links : once the first failing link is known, all flows can be recovered at the same time by the "inferring" node  For failures of SRLG containing at least one adjacent link : recovery time almost equal to local failure detection time (~100ms) – instead of 1s in standard OSPF The iLab.t exp. platform enables i) to control at fine-granularity of (changes in) routing protocol and machine learning component operations wrt network running conditions (key to understand experimental output) and ii) to produce repeatable and reliable results

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5b Virtual Wall Papadimitriou

  • 1. ECODE Usage of IBBT Virtual Wall (iLab.t)
  • 2. SRLG detection and identification from mining of link state protocol data Infer Shared Risk Group (SRLG) from Link state routing information (LSA) arrival pattern to prevent successive SPT re-computation upon shared-risk failure (affects multiple links simultaneously) Current Link-state routing Link-state Routing  Machine Learning 4 8 3 7 2 6 1 5 4 8 3 7 2 6 1 5 First SPT Recomputation LSA(1,2) 4 8 3 7 2 6 1 5 Second SPT Recomputation LSA(7,8) LSA(7,8) Failure Failure 4 8 3 7 2 6 1 5 4 8 3 7 2 6 1 5 Single SPT Recomputation taking into account both link failures LSA(1,2) LSA(7,8) Failure Failure SRG SRG SRG SRG time LSA(1,2) LSA(7,8) receive predict LSA link [1,2] and [7,8] share the same risk (belong to the same SRG)
  • 3.
  • 4.
  • 5.
  • 6.