Skip to main content
Log in

Queuing network of scale free topology: on modelling large scale network

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The analytical performance model of networks with scale free structure is studied in this paper. The key issue is the mathematical relation between the performance measure and the network structure. A stochastic model of closed queuing network (SQN) within which customer routing between queues may depend on the local information of complex network is presented. In the model, the complex network is decomposed into sub-networks with scale-free characteristics called SN. Given the rule of preferential attachment, the routing probabilities allowed are formulated by the rational functions of the degrees of various neighbors which reside within SN. It is proved that the introduction of these functions will preserve the product form of the equilibrium state distribution. The product form yields the convolution expression of normalizing constant accordingly. A recursive algorithm is adopted to solve the expression effectively. Therefore, the performance measures are presented based on the exact solution of the normalizing constant. Finally, the model is applied to the design and evaluation of communication infrastructure of real large-scale network deployed on Internet.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):409–410

    Article  Google Scholar 

  2. Barábási A-L, Albert R, Jeong H (2000) Scale-free characteristics of random networks: the topology of the world-wide web. Phys A: Stat Mech Appl 281(1–4):69–77

    Article  Google Scholar 

  3. Faloutsos M, Faloutsos P, Faloutsos C (1999) On power-law relationships of the Internet topology. In: Proceedings of the conference on applications, technologies, architectures, and protocols for computer communication. ACM, New York

    Google Scholar 

  4. Tangmunarunkit H et al (2002) Network topologies, power laws, and hierarchy. ACM SIGCOMM Comput Commun Rev 32(1):76

    Article  Google Scholar 

  5. Mahadevan P et al (2006) Systematic topology analysis and generation using degree correlations. ACM SIGCOMM Comput Commun Rev 36(4):135–146

    Article  Google Scholar 

  6. Oliveira RV, Zhang B, Zhang L (2007) Observing the evolution of internet as topology. ACM SIGCOMM Comput Commun Rev 37(4):313–324

    Article  Google Scholar 

  7. Li L et al (2004) A first-principles approach to understanding the internet’s router-level topology. In: Proceedings of the 2004 conference on applications, technologies, architectures, and protocols for computer communications, pp 3–14

  8. Chang H, Jamin S, Willinger W (2003) Internet connectivity at the AS-level: an optimization-driven modeling approach. In: Proceedings of the ACM SIGCOMM workshop on models, methods and tools for reproducible network research MoMeTools’03. ACM, New York

    Google Scholar 

  9. Gkantsidis C, Mihail M, Saberi A (2003) Conductance and congestion in power law graphs. ACM SIGMETRICS Perform Eval Rev 31(1):148–159

    Article  Google Scholar 

  10. Priya M et al (2007) Orbis: rescaling degree correlations to generate annotated internet topologies. In: Proceedings of the 2007 conference on applications, technologies, architectures, and protocols for computer communications. ACM, New York

    Google Scholar 

  11. Kameda H, Zhang Y (1995) Uniqueness of the solution for optimal static routing in open BCMP queueing networks. Math Comput Model 22(10–12):119–130

    Article  MATH  MathSciNet  Google Scholar 

  12. Squillante MS, Xia CH, Zhang L (2002) Optimal scheduling in queuing network models of high-volume commercial web sites. Perform Eval 47(4):223–242

    Article  MATH  Google Scholar 

  13. Javadi B, Akbari MK, Abawajy JH (2007) Analytical communication networks model for enterprise grid computing. Future Gener Comput Syst 23(6):737–747

    Article  Google Scholar 

  14. Yin C-Y et al (2006) Efficient routing on scale-free networks based on local information. Phys Lett A 351(4–5):220–224

    Article  MATH  Google Scholar 

  15. Baskett F et al (1975) Open, closed, and mixed networks of queues with different classes of customers. J ACM 22(2):248–260

    Article  MATH  MathSciNet  Google Scholar 

  16. Masahiko, Masayuki, Hideo (1998) Analysis and modeling of World Wide Web traffic for capacity dimensioning of Internet access lines. Perform Eval 34(4):249–271

    Article  Google Scholar 

  17. Mitra D, Wang Q (2005) Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management. IEEE/ACM Trans Netw 13(2):221–233

    Article  Google Scholar 

  18. Che H et al (2006) An integrated, distributed traffic control strategy for the future internet. In: Proceedings of the 2006 SIGCOMM workshop on Internet network management INM’06. ACM, New York

    Google Scholar 

  19. Movsichoff BA, Lagoa CM, Che H (2007) End-to-end optimal algorithms for integrated QoS traffic engineering, and failure recovery. IEEE/ACM Trans Netw 15(4):813–82

    Article  Google Scholar 

  20. Casale G (2006) An efficient algorithm for the exact analysis of multiclass queueing networks with large population sizes. In: Proceedings of the joint international conference on measurement and modeling of computer systems. ACM, New York

    Google Scholar 

  21. Chandy KM, Howard JH, Towsley DF (1977) Product form and local balance in queueing networks. J ACM (JACM) 24(2):250–263

    Article  MATH  MathSciNet  Google Scholar 

  22. Kobayashi H, Gerla M (1983) Optimal routing in closed queuing networks. ACM Trans Comput Syst 1(4):294–310

    Article  Google Scholar 

  23. Harrison PG (1990) The representation of multistage interconnection networks in queuing models of parallel systems. J ACM 37(4):863–898

    Article  MATH  Google Scholar 

  24. Chandy KM, Herzog U, Woo L (1975) Approximate analysis of general queuing networks. IBM J Res Develop 19(1):43–49

    Article  MATH  MathSciNet  Google Scholar 

  25. Bambos N, Michailidis G (2005) Queueing networks of random link topology: stationary dynamics of maximal throughput schedules. Queueing Syst 50(1):5–52

    Article  MATH  MathSciNet  Google Scholar 

  26. Towsley D (1980) Queuing network models with state-dependent routing. J ACM (JACM) 27(2):323–337

    Article  MATH  MathSciNet  Google Scholar 

  27. Nelson RD (1993) The mathematics of product form queuing networks. ACM Comput Surv (CSUR) 25(3):339–369

    Article  Google Scholar 

  28. Buzen JP (1973) Computational algorithms for closed queueing networks with exponential servers. Commun ACM 16(9):527–531

    Article  MATH  MathSciNet  Google Scholar 

  29. Reiser M, Lavenberg SS (1980) Mean-value analysis of closed multichain queuing networks. J ACM (JACM) 27(2):313–322

    Article  MATH  MathSciNet  Google Scholar 

  30. Albert RHJ, Barábási A (1999) Diameter of the World Wide Web. Nature 401:130–131

    Article  Google Scholar 

  31. Tangmunarunkit H et al (2002) Network topology generators: degree-based vs structural. ACM SIGCOMM Comput Commun Rev 32(4):147–159

    Article  Google Scholar 

  32. Dan L, Yuan-Da C, Chun-Qing L (2008) Liana: service-oriented overlay network for performance-cost optimization of grid service. J Supercomput 49(1):127–156

    Google Scholar 

  33. Peterson L et al (2002) A Blueprint for Introducing Disruptive Technology into the Internet. In: Proceedings of ACM HotNets-I Workshop

  34. Park K, Pai VS (2006) CoMon: a mostly-scalable monitoring system for PlanetLab. ACM SIGOPS Oper Syst Rev 40(1):65–74

    Article  Google Scholar 

  35. Barábási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509

    Article  MathSciNet  Google Scholar 

  36. Liu D, Cao Y (2007) CGA: chaotic genetic algorithm for fuzzy job scheduling grid environment. Lecture notes in computer science, vol 4456. Springer, Berlin, p 133

    Google Scholar 

  37. Zhang L, Ardagna D (2004) SLA based profit optimization in autonomic computing systems. In: The 2nd international conference on service oriented computing. ACM, New York

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dan Liu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, D., Cao, YD. Queuing network of scale free topology: on modelling large scale network. J Supercomput 59, 993–1018 (2012). https://doi.org/10.1007/s11227-010-0482-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-010-0482-3

Keywords

Navigation