1 / 21

Enhancing User-Level Path Diagnosis in Networks: TULIP's Approach to Fault Detection and Analysis

TULIP (User-level Path Diagnosis) empowers users to effectively diagnose network performance issues affecting their connections. By utilizing packet-based solutions and out-of-band measurement techniques, it enables the detection of queuing delays, packet loss, and fault localization across network paths. TULIP employs binary and parallel search methods to balance diagnostic accuracy and time efficiency. With an impressive consistency in results, it assures users can identify and report network faults, ultimately fostering improved communication with ISPs and network operations centers.

oakley
Download Presentation

Enhancing User-Level Path Diagnosis in Networks: TULIP's Approach to Fault Detection and Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. User-level Internet Path DiagnosisR. Mahajan, N. Spring, D. Wetherall and T. Anderson

  2. The network is a black box…...so what can I do • We want the users to be able to diagnose their paths • Communicate information to ISP or NOC to improve the network

  3. TULIP: User-level path diagnosis Objectives: Detect performance faults that affect a user’s flows. This involves a measure of the magnitude of the fault (queuing delay, loss) and the localization of the faulty link.

  4. How TULIP does it • Ideal Architecture – Packet based solutions Each router the packet traverses adds a certain number of information to the packet: timestamp, global address of the router’s input interface. Issue: Packet size increases at each hop. A packet loss involves a loss of all the information. Corruption of a packet might yield to incorrect diagnosis data (allthough most corruption are treated as losses)

  5. Because things are never ideal • Basic architecture sufficient for data collection Assets: Fixed packet size and sufficient information… Assuming : stationarity of paths (paths between source and destination don’t change too often)

  6. Diagnosis tools in use in TULIP • Out-of-band measurement probes (or TTL based search) • obtain the Sample TTL and Interface ID • ICMP • Router timestamp • IP identifiers • Approximation of the per-flow counter

  7. How to detect path loss/reordering Sending two probes to determine the behavior of the remote router

  8. Packet queuing An ICMP timestamp is used to determine the queuing delays within a router (median)

  9. The TULIP methods • To perform the measurement, TULIP uses two “scanning” methods. • Binary search (reduces diagnostic traffic but at a cost of diagnosis time) • Parrallel search (interleaves measurements to different routers by cycling through them in nodes)

  10. Network Load and Diagnosis Time • Because of the relative stationary behavior of a router, with an approximative diagnosis time of 10/30 min, TULIP can provide accurate results. • The load for Binary search is B/W and for parrallel LB/W (lower bound) L: # of measurable routers B: Bandwitdth cost of the probes W: Wait time (usually 1s)

  11. 1 1’ 2’ 2 1 2 3 Rank(G)=2 Diagnosing granularity • The granularity is the weighted average of the lengths of its diagnosable segments.

  12. Various granularity for different measurements • 50 % of the paths have a granularity less than 3 hops (75% <4) • TULIP matches ideal tomography implementation

  13. Validation • Compared results with Planet Lab coupled with a tomography system • Use a measure “rate delta” that computes the difference between the rate at the far end minus that at the near end of a segment. Negative values implies a lack of consistency (values spawn a range too large)

  14. Reordering Results 85 % of the results are consistent for forward path 75 % for round trip (due to the asymmetric nature of some paths)

  15. Loss results • 85% again of non negative deltas • Round trip counterpart less affected by asymmetry than the Reordering diagnosis (because loss usually occurs close to the destination)

  16. Queuing Results • ICMP message generation has a poor timestamp resolution (the two median within 2ms of each other – One from TCPDump on planet lab and one from TULIP). • Forward path shows that queuing delay is consistent (very few negative values) • Round trip reflects the variability in the return path

  17. The last mile… • First hops from user is the bottleneck

  18. Persistance of a fault • We check for how many iterations, TULIP yields similar results • 80% of the path show faults persisting long enough for TULIP to diagnose them (typical time a binary search takes to locate a fault : 6 runs)

  19. Conclusions • Network Operators would be able to diagnose links efficiently • And a user too … if the world was populated entirely by Computer nerds.

  20. Issues… • Multiple TULIP users could reduce the accuracy of the probing method, the per flow counter • An application doesn’t experience the network the same way an active measurement does. (TCP, application dependant as well as flags)

  21. …and possible improvements • Per flow counter at the router level (unrealistic) • Hash source address and IPID (for flow) • ICMP timestamp have reception time as well as transmission time (allows the calculation of the delay the packet is processed at the router)

More Related