Diagnosing Spatio-Temporal Internet Congestion Properties

1. Diagnosing Spatio-Temporal Internet Congestion Properties Leiwen Deng Aleksandar Kuzmanovic EECS Department Northwestern University http://networks.cs.northwestern.edu

2. Problem • Detect congestion events on an end-to-end path and reveal their spatio-temporal properties: • Where they happen (edge, core, intra-AS, inter-AS)? • How long they last / frequently occur? S D

3. Why Do We Care? • Fault diagnosis • Advanced congestion control • Distributed monitoring systems • Overlay design • We want to know! S D

4. Challenges • Congestion events relatively infrequent • Measure queuing delay instead of Ploss • No/low support from the network • Combine e2e with probes to intermediate nodes • Path asymmetry • Measurements still possible via “measurable pairs”

5. Outline • Methodology • Implementation (Pong) • Validation • Measurements • Results

6. Methodology Highlights • Coordinated probing • Send 4, 3, or 2 packets from two endpoints • Quality of Measurability (QoM) • Able to deterministically detect its own inaccuracy • Self-adaptivity • Switch between different probing schemes based on QoM and path properties

7. f s d b Coordinated Probing Probe S D f probe b probe , s probe d probe , , 4-p probing: a symmetric path scenario

8. f s d b Locating Congestion Points Tracing Congestion Status Half-path queuing delay Coordinated Probing Probe Δf Δd S D Δs Δb Δfs Δfd

9. Probe Probe Probe Probe Probe Δfs Δfd Δfs Δfd Δfs Δfs Δfs Δfd Δfd Δfd Locating Congestion Points 1. Probe Scheduling S D Sequentially probe (4-p) nodes on the path

10. Probe Probe Congestion Detect Switch Point Locating Congestion Points 2. Switch Point Approach S D Correlate probes to neighboring nodes

11. Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Probe Congestion Tracing Congestion Status S D Link 1 (Located Congestion Point) Congestion Status Link 1 Time Reuse probes sent to un-congested routers

12. f Congestion s D S d Measurable Pair b Complementary d probe Measurable Pairs 4-p probing scenario

13. f Congestion s D S d Δf +Δb ≈Δs +Δd Condition: Measurable Pair b Complementary d probe |(Δf +Δb) − (Δs +Δd)| QoM4p = 1 − max(Δf +Δb, Δs +Δd) Quality of Measurability

14. Experiments • 400 PlanetLab nodes • Measure each pair for 1 hour • 23,351 paths within 8 days

15. Results • Edge vs. core • Edge more frequently congested than the core: 14 times on average • Intra-AS vs. Inter-AS • Edge: Intra-AS > Inter-AS • Core: Intra-AS < Inter-AS • Time domain • Edges: congestion events clustered in time • Core: congestion events dispersed in time • Links vs. Paths • Links: 12% congested, 3% considerably • Paths: 20% considerably congested

16. Conclusions • Spatio-temporal Internet congestion properties • New methodology • Coordinated probing • Detect its own inaccuracy • Self adaptive to path properties • Handles path asymmetries • Implemented, deployed, evaluated, measured • High accuracy in both spatial and temporal domains • Future work: • Triggered monitoring system to learn more