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FIFO Queueing Policies for Packets with Heterogeneous Processing

  • Kirill Kogan
  • Alejandro López-Ortiz
  • Sergey I. Nikolenko
  • Alexander V. Sirotkin
  • Denis Tugaryov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7659)

Abstract

We consider the problem of managing a bounded size First-In-First-Out (FIFO) queue buffer, where each incoming unit-sized packet requires several rounds of processing before it can be transmitted out. Our objective is to maximize the total number of successfully transmitted packets. We consider both push-out (when the policy is permitted to drop already admitted packets) and non-push-out cases. In particular, we provide analytical guarantees for the throughput performance of our algorithms. We further conduct a comprehensive simulation study which experimentally validates the predicted theoretical behaviour.

Keywords

scheduling buffer management first-in-first-out queueing switches online algorithms competitive analysis 

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References

  1. 1.
    Aiello, W., Mansour, Y., Rajagopolan, S., Rosén, A.: Competitive queue policies for differentiated services. Journal of Algorithms 55(2), 113–141 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  2. 2.
    Albers, S., Jacobs, T.: An experimental study of new and known online packet buffering algorithms. Algorithmica 57(4), 725–746 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  3. 3.
    Albers, S., Schmidt, M.: On the performance of greedy algorithms in packet buffering. SIAM Journal on Computing 35(2), 278–304 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
  5. 5.
    Azar, Y., Litichevskey, A.: Maximizing throughput in multi-queue switches. Algorithmica 45(1), 69–90 (2006)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Azar, Y., Richter, Y.: An improved algorithm for CIOQ switches. ACM Transactions on Algorithms 2(2), 282–295 (2006)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Borodin, A., El-Yaniv, R.: Online Computation and Competitive Analysis. Cambridge University Press (1998)Google Scholar
  8. 8.
    Brucker, P., Heitmann, S., Hurink, J., Nieberg, T.: Job-shop scheduling with limited capacity buffers. OR Spectrum 28(2), 151–176 (2006)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Cavium. OCTEON II CN68XX multi-core MIPS64 processors, product brief (2010), http://www.caviumnetworks.com/OCTEON-II_CN68XX.html
  10. 10.
    Cisco. The cisco QuantumFlow processor, product brief (2010), http://www.cisco.com/en/US/prod/collateral/routers/ps9343/solution_overview_c22-448936.html
  11. 11.
    Englert, M., Westermann, M.: Lower and upper bounds on FIFO buffer management in QoS switches. Algorithmica 53(4), 523–548 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    EZChip. NP-4 network processor, product brief (2010), http://www.ezchip.com/p_np4.htm
  13. 13.
    Goldwasser, M.: A survey of buffer management policies for packet switches. SIGACT News 41(1), 100–128 (2010)CrossRefGoogle Scholar
  14. 14.
    Keslassy, I., Kogan, K., Scalosub, G., Segal, M.: Providing performance guarantees in multipass network processors. In: INFOCOM, pp. 3191–3199 (2011)Google Scholar
  15. 15.
    Kesselman, A., Patt-Shamir, B., Scalosub, G.: Competitive buffer management with packet dependencies. In: Proceedings of the 23rd IEEE International Parallel and Distributed Processing Symposium, IPDPS (2009)Google Scholar
  16. 16.
    Kesselman, A., Kogan, K., Segal, M.: Improved Competitive Performance Bounds for CIOQ Switches. In: Halperin, D., Mehlhorn, K. (eds.) ESA 2008. LNCS, vol. 5193, pp. 577–588. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  17. 17.
    Kesselman, A., Kogan, K., Segal, M.: Packet mode and QoS algorithms for buffered crossbar switches with FIFO queuing. Distributed Computing 23(3), 163–175 (2010)zbMATHCrossRefGoogle Scholar
  18. 18.
    Kesselman, A., Lotker, Z., Mansour, Y., Patt-Shamir, B., Schieber, B., Sviridenko, M.: Buffer overflow management in QoS switches. SIAM Journal on Computing 33(3), 563–583 (2004)MathSciNetzbMATHCrossRefGoogle Scholar
  19. 19.
    Kogan, K., López-Ortiz, A., Nikolenko, S.I., Sirotkin, A.V., Tugaryov, D.: FIFO queueing policies for packets with heterogeneous processing. arXiv:1204.5443 [cs.NI] (2012), http://arxiv.org/abs/1204.5443
  20. 20.
    Kogan, K., López-Ortiz, A., Scalosub, G., Segal, M.: Large profits or fast gains: A dilemma in maximizing throughput with applications to network processors (2012), http://arxiv.org/abs/1202.5755
  21. 21.
    Leonardi, S., Raz, D.: Approximating total flow time on parallel machines. In: STOC, pp. 110–119 (1997)Google Scholar
  22. 22.
    Mansour, Y., Patt-Shamir, B., Lapid, O.: Optimal smoothing schedules for real-time streams. Distributed Computing 17(1), 77–89 (2004)CrossRefGoogle Scholar
  23. 23.
    Mansour, Y., Patt-Shamir, B., Rawitz, D.: Overflow management with multipart packets. In: INFOCOM, pp. 2606–2614 (2011)Google Scholar
  24. 24.
    McKeown, N., Parulkar, G., Shenker, S., Anderson, T., Peterson, L., Turner, J., Balakrishnan, H., Rexford, J.: OpenFlow switch specification (2011), http://www.openflow.org/documents/openflow-spec-v1.1.0.pdf
  25. 25.
    Motwani, R., Phillips, S., Torng, E.: Non-clairvoyant scheduling. Theoretical Computer Science 130(1), 17–47 (1994)MathSciNetzbMATHCrossRefGoogle Scholar
  26. 26.
    Muthu Muthukrishnan, S., Rajaraman, R., Shaheen, A., Gehrke, J.E.: Online scheduling to minimize average stretch. SIAM Journal on Computing 34(2), 433–452 (2005)CrossRefGoogle Scholar
  27. 27.
    Paxson, V., Floyd, S.: Wide area traffic: the failure of poisson modeling. IEEE/ACM Trans. Netw. 3(3), 226–244 (1995)CrossRefGoogle Scholar
  28. 28.
    Pruhs, K.: Competitive online scheduling for server systems. SIGMETRICS Performance Evaluation Review 34(4), 52–58 (2007)CrossRefGoogle Scholar
  29. 29.
    Ruiz, R., Vázquez-Rodrígue, J.A.: The hybrid flow shop scheduling problem. European Journal of Operational Research 205(1), 1–18 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  30. 30.
    Schrage, L.: A proof of the optimality of the shortest remaining processing time discipline. Operations Research 16, 687–690 (1968)zbMATHCrossRefGoogle Scholar
  31. 31.
    Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Communications of the ACM 28(2), 202–208 (1985)MathSciNetCrossRefGoogle Scholar
  32. 32.
    Veres, A., Boda, M.: The chaotic nature of TCP congestion control. In: INFOCOM, pp. 1715–1723 (2000)Google Scholar
  33. 33.
    Wolf, T., Pappu, P., Franklin, M.A.: Predictive scheduling of network processors. Computer Networks 41(5), 601–621 (2003)zbMATHCrossRefGoogle Scholar
  34. 34.
    Xelerated. X11 family of network processors, product brief (2010), http://www.xelerated.com/Uploads/Files/67.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kirill Kogan
    • 1
  • Alejandro López-Ortiz
    • 1
  • Sergey I. Nikolenko
    • 2
    • 3
  • Alexander V. Sirotkin
    • 4
    • 3
  • Denis Tugaryov
    • 3
  1. 1.School of Computer ScienceUniversity of WaterlooCanada
  2. 2.Steklov Mathematical InstituteSt. PetersburgRussia
  3. 3.St. Petersburg Academic UniversitySt. PetersburgRussia
  4. 4.St. Petersburg Institute for Informatics and Automation of the RASSt. PetersburgRussia

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