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Dynamics of Prefix usage at an Edge router

Dynamics of Prefix usage at an Edge router. Kaustubh Gadkari , Dan Massey and Christos Papadopoulos. Outline. Introduction – BGP RIB and FIB growth Motivation Methodology Results Conclusions and future w ork. Outline. Introduction – BGP RIB and FIB growth Motivation Methodology

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Dynamics of Prefix usage at an Edge router

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  1. Dynamics of Prefix usage at an Edge router Kaustubh Gadkari, Dan Massey and Christos Papadopoulos

  2. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  3. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  4. Inter-Domain Routing BGP 129.82/16, 129.82/18 … 74.125/16, … CSU Google

  5. BGP Tables Router Memory Routing Updates Routing Table (RIB) Routing Updates (Prefix, Path) (Prefix, Outgoing Interface, Next Hop) Line Card Line Card Line Card Forwarding Table (FIB) Forwarding Table (FIB) Forwarding Table (FIB)

  6. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  7. Table Growth • The size of the global routing is growing rapidly. • Increasing routing table size requires more memory on routers. • Operators are forced into faster upgrade cycles. http://bgp.potaroo.net/as6447/

  8. Implications of Table Growth • RIB size affects FIB size. • FIB scaling is arguably more important. • FIBs stored on line card memory, which is smaller and more expensive than main memory.

  9. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  10. Motivation • Some current research focuses on scaling the FIB by storing partial forwarding information. • But how to choose prefixes in a reduced FIBs? • Prefixes receiving most packets should probably be in the table. • But are there better criteria to define a dominant set? • How does it behave?

  11. Motivation (contd.) • Previous work focused on prefix popularity over days or weeks. • Tradeoff that prefers ease of selection. • Optimum prefix selection is a hard problem. • Factors: traffic volume, activity patterns and interplay of traffic dynamics • This work: understand prefix dynamics better.

  12. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  13. Methodology • Monitor links to two tier-1 provider links (1Gb/s each) at a regional ISP. • Dataset: two simultaneous 24-hour packet traces from these links. • Use outgoing packets only.

  14. Old Metric: Global Rank • Rank prefixes according to number of packets during the full 24-hour trace. • This is the prefix’s global rank. • Plot number of prefixes that account for a given fraction of packets. • Results corroborate previous studies.

  15. Measuring Prefix Dynamics • Split traffic trace into small intervals (5 min). • Rank prefixes in each interval according to number of packets. • We call this the prefix’s interval rank.

  16. New Metrics • Duty cycle • Fraction of the total number of intervals in which the prefix receives at least one packet. • Mean rank difference • Variation of a prefix’s interval rank from its global rank.

  17. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  18. Duty Cycle • Measure of prefix’s activity. ~24,000 prefixes High duty cycle, high traffic High duty cycle, low traffic ~200 prefixes ~10 prefixes ~56,000 prefixes Low duty cycle, high traffic Low duty cycle, low traffic Global Prefix Rank

  19. Duty Cycle Observations • Popular prefixes have high duty cycles. • Always get packets. • Several popular prefixes have a duty cycle of > 90%.

  20. Mean Rank Difference • Measure of prefix’s “busy-ness”. 60% of all prefixes, 5% of all traffic Generally Unpopular Prefixes Less than 1% of all prefixes, 40% of all packets Stable Prefixes 5% of all prefixes, 55% of all packets Generally Popular Prefixes Global Prefix Rank

  21. Outline • Introduction – BGP • RIB and FIB growth • Motivation • Methodology • Results • Conclusions and future work

  22. Conclusions • Understanding dynamic behavior of FIB prefixes is important for reduced-FIB designs. • Proposed two new metrics: Duty cycle and mean rank difference • We corroborated previous work showing set of dominant prefixes is small. • New metrics characterize the dominant set better, which is generally active and busy. • Majority of the prefixes have very low activity opening up caching opportunities. • Results encouraging in terms of developing reduced FIB designs.

  23. Future Work • Investigate prefix dynamics at other ISPs. • Investigate prefix dynamics at different intervals. • Develop a design for efficient forwarding using a reduced FIB.

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