Towards Efficient Large-Scale VPN Monitoring and Diagnosis under Operational Constraints Yao Zhao, Zhaosheng Zhu, Yan Chen, Northwestern University Dan Pei, Jia Wang, AT&T Labs -Research

Page 2 Outline Motivation Problem Definition Monitor Setup Single-round monitoring Multi-round monitoring Evaluation Related Works Conclusion

Page 3 Motivation PE VPN Backbone PE CE VPN 1, Site 2 VPN 2, Site 1 VPN 1, Site 1 PE CE VPN 2, Site 2

Page 4 Motivation VPN performance monitoring Reliability Quality of service (SLA) Approaches Passive measurements: SNMP-based Monitoring – Fixed poll rate – Difficult to measure end-to-end path-level features (e.g. delay, bw) Active measurements – Operational constraints E.g. monitor, link, path constraints

Page 5 Problem Definition PE VPN Backbone PE CE VPN 2, Site 2 VPN 2, Site 1 VPN 1, Site 1 PE CE VPN 1, Site 2 Goal: continuously monitoring and diagnosing VPN performance under operational constraints Each monitor can measure <=c paths Each replier can reply <=r paths Each link is on <=b measured paths Traffic isolation between VPNs Challenges with operational constraints Optimization problem → constraint satisfactory problem All paths measured simultaneously? X

Page 6 VScope System Architecture Two phases: VScope Setup VScope Operation: monitoring + diagnosis Provides a smooth tradeoff between measurement frequency and monitors deployment/management costs

Page 7 Two Phases Monitor setup phase From certain monitor candidates, how to select minimal number of monitors, which in the measurement phase can measure a selected set of paths that covers all links in the network under the given measurement constraints? NP-hard even without considering constraints Monitoring and fault diagnosis phase When faulty paths are discovered in the path monitoring phase, how to quickly select some paths under the operational constraints to be further measured so that the faulty link(s) can be accurately identified?

Page 8 Two Phases Monitor setup phase From certain monitor candidates, how to select minimal number of monitors, which in the measurement phase can measure a selected set of paths that covers all links in the network under the given measurement constraints? NP-hard even without considering constraints Monitoring and fault diagnosis phase When faulty paths are discovered in the path monitoring phase, how to quickly select some paths under the operational constraints to be further measured so that the faulty link(s) can be accurately identified?

Page 9 Outline Motivation Problem Definition Monitor Setup Single-round monitoring Multi-round monitoring Evaluation Related Works Conclusion

Page 10 Monitoring Strategies … P1P1 … P2P2 … P3P3 … P4P4 … P5P5 … P6P6 … P1P1 … P2P2 … P3P3 … P4P4 … P5P5 … P6P6 t t Single-Round Monitoring Multi-Round Monitoring Round 1 Round 2 Round 1

Page 11 Multi-Round Monitoring Pros Relax tight constraints Reduce number of monitors Cons Less monitoring frequency Monitor Selection Algorithm Consider R rounds of back-to-back measurements Step 1: convert multi-round monitor selection problem to single-round problem and solve the single-round monitor selection problem – Relax monitor & link bw constraints by a factor of R Step 2: schedule paths measured in R rounds

Page 12 Single-Round Monitor Selection Monitor Selection Problem Related to Minimum Set Cover problem NP-hard without constraints [Bejerano, Infocom03] Pure Greedy Algorithm Simple and locally optimized Greedy Assisted Integer Linear Programming based algorithm Linear programming is good at dealing with constraints ILP is NP-hard Need to relax ILP to LP

Page 13 Pure Greedy Algorithm Two-level nested Minimum Set Cover Problem and Maximum Coverage Problem Iteratively select a candidate router as a new monitor that can measure paths covering maximum number of un-covered links before the selection Computing the maximum gain of adding a router as a monitor is a variant of Maximum Coverage problem (also NP-hard) – Iteratively select a path of the router that will not violate the link bandwidth constraints and covers maximum number of un-covered links before the selection – Until the number of selected paths reaches the monitor’s constraint

Page 14 Integer Linear Programming Minimize number of monitors A path is monitored iff the source router is selected as monitor Monitor constraintReplier constraint A link is covered if at least one path containing the link is selected Link bandwidth constraint It is NP-hard!

Page 15 Relaxation with Random Rounding Relax the Integer Linear Programming to Linear Programming Suppose the solution of linear programming is x * i, y * i Rounding rule:

Page 16 Greedy Assisted Linear Programming Use Linear Programming to select a set of monitors and corresponding measurement paths Not all links are covered Use greedy algorithm to cover uncovered links Similar to the pure greedy algorithm

Page 17 Mulit-Round Path Scheduling NP-hard Can reduce minimum graph coloring problem to path scheduling problem Three algorithms Random algorithm – Randomly schedule paths independently – Run random algorithm multiple times to get the best one Greedy algorithm – Minimize link utilization in every step LP based Randomization Algorithm – ILP + relaxation and random rounding Optimization metrics Maximum link violation degree (MLVD) Average link violation degree (ALVD)

Page 18 Outline Motivation Problem Definition Monitor Setup Single-round monitor selection Multi-round monitor selection Evaluation Related Works Conclusion

Page 19 Evaluation Topologies Synthetic topologies generated by BRITE Real topologies from a tier-1 ISP: one IP backbone topology (IP-EX), one VPN backbone topology (VB), and two VPN infrastructure topologies (V1-EX, V2-EX) – Scale from 100s nodes to 100,000s nodes – Heterogeneous real link bw (1.54Mbps ~ 10Gbps) Operational constraints From ISP management team – E.g. percent link bw allowed for probing: 1% Evaluation metrics Percentage of monitors selected Maximum (average) link violation degree after scheduling Running speed

Page 20 Experimental setup Default configuration Monitor constraint = 12 Replier constraint = 24 Probing rate per path = 4 pkt /sec Measurement BW consumed per path = 1.6Kbps Link constraint = 1% x (link capacity)

Page 21 Baseline Monitor Selection Results (VB Topology) LP+Greedy selects fewer monitors. Vary Link Constraint Vary Monitor Constraint

Page 22 Multi-Round Monitor Selection Results (V1-EX Topology) More rounds and fewer monitors and diminishing returns. Vary Link Constraint Vary Monitor Constraint

Page 23 Multi-Round Monitor Selection Results (V1-EX Topology) LP > Random > Greedy. Link violation degree Percentage of links with violation Greedy Random LP

Page 24 Related Work Path Selection The monitoring problem is not considered or too simple Complex path selection goal (basis, SVD, Bayesian experimental design) Monitoring Placement Active Monitoring Systems – Similar problem without operational constraints [Bejerano, Infocom03] – Robustness consideration Passive Monitoring Systems – SNMP Polling – Traffic sampling

Page 25 Conclusions VScope for continuously monitoring & diagnosis Consider operational constraints Design multi-round monitor selection algorithms – Single-round monitor selection – Monitoring path scheduling Evaluated with synthetic and real topologies – Our algorithms are efficient in minimizing number of monitors with low constraint violation

Q & A? Thanks!