Jigsaw: Solving the Puzzle of Enterprise 802.11 Analysis Yu-Chung Cheng John Bellardo, Peter Benko, Alex C. Snoeren, Geoff Voelker, Stefan Savage.

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Presentation transcript:

Jigsaw: Solving the Puzzle of Enterprise Analysis Yu-Chung Cheng John Bellardo, Peter Benko, Alex C. Snoeren, Geoff Voelker, Stefan Savage

2 Enterprise ? Easy. Blanket the building with APs for 100% coverage

3 A familiar story... “The wireless is being flaky.” “Flaky how?” “Well, my connections got dropped earlier and now things seem very sloooow.” “OK, we will take a look” “Wait, wait … it’s ok now” “Mmm… well let us know if you have any more problems.” Now what? Employee Support

4 What are the problems?  Contention with nearby wireless devices?  Bad AP channel assignments?  Microwave ovens?  Congestions in the Internet?  Bad interaction between TCP and ?  Rogue access points?  Poor choice of APs (weak signal)?  Incompatible user software/hardware?  DoS attack?! …… Need to monitor the wireless network across time, locations, channels, and protocol layers

5 How to monitor ? MeasurementLimitations AP tracesOnly packets that AP sees 1 passive snifferLimited coverage N passive sniffers in 1 channel Limited frequency (roaming, broadband interference, AP channel assignments) N passive sniffers of all channels Need synchronized traces

6 Jigsaw  Measure real large wireless networks  Collect every possible information PHY/Link/IP/TCP/App layer trace Collect every single wireless packet  Need many sniffers for 100% coverage  Provide global view of wireless networks across time, locations, channels, and protocol layers

7 New CSE building at UCSD  150k square feet  4 floors  >500 occupants  150 faculty/staff  350 students  Building-wide WiFi  39 access points  b/g Channel 1, 6, 11  active clients anytime  Daily traffic ~5 GB

8 UCSD passive monitor system  Overlays existing WiFi network  Series of passive sniffers  Blanket deployment over 4 floors  39 sensor pods (156 radios)  4 radios per pod, cover all channels in use  Captures all activities Including CRC/PHY events  Stream back over wired network to a centralized storage

9 Jigsaw design Traces synchronization and unification L2 state reconstruction TCP flow reconstruction

10 Synchronization  Create a virtual global clock  To keep unification working  Critical evidence for analysis If A and B are transmitting at the same time they could interfere If A starts transmitting after B has started then A can’t hear B  Require fine time-scales (10-50us)  NTP is >100 usec accuracy  HW clocks (TSF) have 100PPM stability Time (s) TSF diff (us) TSF diff of two sniffers

11 Traces synchronization and unification  Sniffers label packets w/ local timestamp (TSF)  Need a global clock  Estimate the offset between TSF and the global clock for each sniffer

12 Trace unification (ideal) Time

13 Trace unification (reality) Time JFrame 1JFrame 4JFrame 5JFrame 3JFrame 2 Jigsaw unified trace

14 Challenge: sync at large-scale  How to bootstrap?  Goal: estimate the offset between TSF and the global clock for each sniffer  Time reference from one sniffer to the other  Sync across channels  Dual radios on same sniffer slaved to same clock  Manage TSF clock skews  Continuously re-adjust offsets when unifying frames ToTo 1234 ∆t 1 ∆t 2

15 Jigsaw in action  Jigsaw unifies 156 traces into one global trace  Covers 99% of AP frames, 96% of client frames StartsJan 24,2006 (Tuesday) Duration24 hr Total APs107 (39 CSE) CSE Clients1026 Active CSE clients anytime Total Events2,700M PHY/CRC Errors48% Valid Frames52% JFrames530M Events per Jframe 2.97

16 L2-ACK Beacon Synchronized Valid packets CRC errors PHY errors

17 Jigsaw syncs 99% frames < 20us  Measure sync. quality by max dispersion per Jframe  20 us is important threshold  back-off time is 20 us  inter frame time is 50 us  Sufficient to infer many events

18 Hidden terminal problems  Infer transmission failure by absence of ACK  Estimate conditional probability of loss given simultaneous transmission by some hidden- terminal senderreceiverhidden terminal  How much packet is lost due to hidden- terminal? ?

19 Hidden Terminal Problems  10% of sender-receiver pairs have over 10% losses due to hidden terminals

20 Trace analysis b/g interactions ARP Broadcast Storms TCP loss rate in wireless vs. in Internet Microwave Ovens

21 Moving forward  Developed “Jigsaw” that allows  24x7 monitor system in UCSD CSE w/ 156 sniffers  Global fine-grained view of large wireless network (time, locations, channels)  Jigsaw software will be available shortly  Ongoing work  Root cause diagnoses of end-to-end performance in wireless networks  Standard wireless problem analysis Ex. Exposed terminal problems

22 Q & A Live traffic monitoring and more information at