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Input Queued Switches: Cell Switching vs. Packet Switching

Input Queued Switches: Cell Switching vs. Packet Switching. Abtin Keshavarzian Joint work with Yashar Ganjali, Devavrat Shah Stanford University. VOQ 11. Output 1. Input 1. VOQ 1N. VOQ N1. Output N. Input N. VOQ NN. Background. Switching Fabric. Time is slotted

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Input Queued Switches: Cell Switching vs. Packet Switching

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  1. Input Queued Switches:Cell Switching vs. Packet Switching Abtin Keshavarzian Joint work with Yashar Ganjali, Devavrat Shah Stanford University

  2. VOQ11 Output 1 Input 1 VOQ1N VOQN1 Output N Input N VOQNN Background Switching Fabric • Time is slotted • Data units of fixed size cells • Buffers at input ports (Input-Queued Switch) • To avoid HoL blocking , virtual output queues are used

  3. Motivation Switch • Packets have different lengths • Splitter module • Combiner module (memory) • Packet delays are more important than Cell delays Packet Based Scheduling algorithms VOQ11 Combiner VOQ1N Splitter VOQN1 VOQNN

  4. Outline • Cell based algorithms review: • Stability concept • Maximum Weight Matching algorithm • Packet based algorithms • Packet-Based Algorithms • PB-MWM and its stability • PB Algorithms Classification • Work Conserving • Waiting • Waiting PB Algorithms • Conclusion

  5. VOQ11 Output 1 Input 1 VOQ1N VOQN1 Output N Input N VOQNN Notation – Arrival rate Switching Fabric • : Number of cells arrived to VOQij up to time n • : Number of cells departed from VOQij up to time n • : Number of cells queued at VOQij at time n • (SLLN) almost surely

  6. Admissibility and Rate Stability • The arrival rate matrix is “admissible” iff • A switch under a matching algorithm is “stable” (rate stable) if, almost surely,

  7. MWM algorithm • A matching • MWM: At each time slot, select the matching with maximum weight

  8. MWM Stability • McKeown et al showed that MWM is stable under i.i.d. Bernoulli traffic • Dai and Prabhakar using Fluid model technique showed MWM is stable for any admissible traffic N. McKeown,V. Ananthram, and J. Walrand, “Achieving 100% throughput in an input-queued switch,” INFOCOM 1996, pp. 296-302. J. G. Dai and B. Prabhakar, “The throughput of data switches with or without speedup,” INFOCOM 2000, pp. 556-564.

  9. Outline • Cell based algorithms review: • Stability concept • Maximum Weight Matching algorithm • Packet based algorithms • Packet-Based Algorithms • PB-MWM and its stability • Packet Based Algorithms Classification • Work Conserving • Waiting • Waiting Packet Based Algorithms • Conclusion

  10. Packet-Based Switching • Once the scheduler starts transmitting the first cell of a packet, it continues until the whole packet is received at output port

  11. Packet-Based Switching • Once the scheduler starts transmitting the first cell of a packet, it continues until the whole packet is received at output port

  12. Packet-Based Switching • Once the scheduler starts transmitting the first cell of a packet, it continues until the whole packet is received at output port.

  13. Cell-based to Packet-based • Consider cell-based algorithm X • At each time slot: • Busy ports: middle of sending a packet • Free ports: i/o ports can be assigned freely • PB-X • Keep the assignments used by busy ports • Find a sub-matching for free ports using algorithm X.

  14. Stability of PB-MWM PB-MWM is stable under “regenerative admissible traffic” Traffic is called “regenerative” if on average it requires a finite time to reach the state where all ports are free if it keeps using any fixed matching. • Bernoulli i.i.d. is a regenerative traffic. M.A. Marsan, A. Bianco, P. Giaccone, E. Leonardi, and F. Nari, “Packet Scheduling in Input-Queued Cell-based switches,” INFOCOM 2001, pp. 1085-1094

  15. Proof Outline • Matching m(n) is “k-imperfect” if • For PB-MWM: • Lemma: A scheduling algorithm is rate stable if the average value of its weight is larger than maximum weight matching minus a bounded constant.

  16. Question • CB-MWM is stable under any admissible traffic • PB-MWM is stable under any admissible regenerative traffic. Is the regenerative condition necessary?

  17. Counter-example

  18. Counter-example

  19. Counter-example

  20. Counter-example

  21. Counter-example

  22. Counter-example

  23. Counter-example

  24. Classification of PB algorithms • Work Conserving (non-waiting): • No input is left unmatched when it has a packet for an unmatched output. • Waiting : • Input ports may wait(do not start sending a packet) for infinite number of time slots. No work-conserving algorithm can be rate stable for all admissible traffic.

  25. Segment #2 Segment #1 PB-wMWM • Switch runs at speedup • Maximum packet length: L • If use usual PB-MWM • Else wait till all ports are free. PB-wMWM is rate stable for any admissible traffic with known max packet length

  26. Modified PB-wMWM • The packet length is not known but has bounded expectation • : the maximum length of packets left when waiting starts during lth segment Modified PB-wMWM is rate stable for any admissible traffic with bounded packet length Segment #2 Segment #1

  27. Conclusion • PB-MWM is rate stable under any admissible regenerative traffic. • Work-conserving packet based algorithms can not be rate stable for all admissible traffics •  Waiting is essential • PB-wMWM and its modified version are stable under any admissible traffic (with bounded mean packet length) • Future work: • Find simpler algorithms that are stable for any admissible traffic.

  28. Fluid model • : number of time slots matching m being used up to time n

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