Skip to main content
Log in

Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks

Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

Addressing the problem of queue scheduling for the packet-switched system is a vital aspect of congestion control. In this paper, the fuzzy logic based decision method is adopted for queue scheduling in order to enforce some level of control for traffic of different quality of service requirements using predetermined values. The fuzzy scheduler proposed in this paper takes into account the dynamic nature of the Internet traffic with respect to its time-varying packet arrival process that affects the network states and performance. Three queues are defined, viz low, medium and high priority queues. The choice of prioritizing packets influences how queues are served. The fuzzy scheduler not only utilizes queue priority in the queue scheduling scheme, but also considers packet drop susceptibility and queue limit. Through simulation it is shown that the fuzzy scheduler is more appropriate for the dynamic nature of Internet traffic in a packet-switched system as compared with some existing queue scheduling methods. Results show that the scheduling strategy of the proposed fuzzy scheduler reduces packet drop, provides good link utilization and minimizes queue delay as compared with the priority queuing (PQ), first-in-first-out (FIFO), and weighted fair queuing (WFQ).

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. Sheldon T. Encyclopedia of Networking and Telecommunications (Network Professionals Library). USA: Osborne/McGraw-Hill Press, 2001.

  2. Guo Z, Zeng H. Simulation and analysis of weighted fair queuing algorithms in OPNET. In Proc. ICCMS, Feb. 2009, pp.114–118.

  3. Padjen R, Keefer L, Thurston S et al. Flannagan and Martin Walshaw. Cisco AVVID and IP Telephony Design & Implementation.

  4. Cho H, Fadali M, Lee H. Dynamic queue scheduling using fuzzy systems for Internet routers. In Proc. the 14th IEEE Int. Conf. Fuzzy Systems, May 2005, pp.471–476.

  5. Cho H, Fadali M, Lee J et al (2007) Lyapunov-based fuzzy queue scheduling for Internet routers. Journal of Control, Automation and Systems 5(3):317–323

    Google Scholar 

  6. Bolin N, Lemin L. Novel fuzzy scheduling supporting quality of service for wideband CDMA cellular networks. In Proc. IEEE Int. Conf. Communications, Circuits and Systems, May 2005, pp.368–373.

  7. Gomathy C, Shanmugavel S. An efficient fuzzy based priority scheduler for mobile ad hoc networks and performance analysis for various mobility models. In Proc. IEEE WCNC, March 2004, pp.1087–1092.

  8. Kazemian HB (2006) A fuzzy approach to MPEG video transmission in ATM networks. Fuzzy Sets and Systems 157(16):2259–2272

    Article  MathSciNet  Google Scholar 

  9. Bourenane M, Benhamamouch D, Hamadouch H. Inductive approach for QoS packet scheduling in dynamic networks. In Proc. ICMCS, April 2009, pp.25–30.

  10. Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Management Science 17(4):141–164

    Article  MathSciNet  Google Scholar 

  11. Blake S, Black D, Carlson M et al. An architecture for differentiated services. Request for Comments (RFC) 2475, http://www.hjp.at/doc/rfc/rfc2475.html, Dec. 1998.

  12. Melo Jr. A, Coello J. Packet scheduling based on learning in the next generation Internet architectures. In Proc. the 5th IEEE ISCC, July 2000, pp.773–778.

  13. Kanhere S S, Sethu H. Fair, efficient and low-latency packet scheduling using nested deficit round robin. In Proc. IEEE Workshop on High Performance Switching and Routing, May 2001, pp.6–10.

  14. Wakuda K, Kasahara S. A packet scheduling algorithm for maxmin fairness in multihop wireless LANs. Journal of Computer Communications, May 2009, pp.1437–1444.

  15. Nagle J (1987) On packet switches with infinite storage. IEEE Trans Communication 35(4):435–438

    Article  Google Scholar 

  16. Demers A, Keshav K, Shenker S (1989) Analysis and simulation of a fair queueing algorithm. Comput Commun Rev 19(4):1–12

    Article  Google Scholar 

  17. Stiliadis D, Varma A (1998) Efficient fair queuing algorithm for packet-switched networks. IEEE Trans Networking 6(2):175–185

    Article  Google Scholar 

  18. Kesh S, Nerur S, Ramanujan S (2002) Quality of service — Technology and implementation. Journal of Information Management & Computer Security 10(2):85–91

    Article  Google Scholar 

  19. Zadeh LA (1971) Similarity relations and fuzzy orderings. Information Sciences 3(2):177–200

    Article  MathSciNet  MATH  Google Scholar 

  20. Cordon O, Herrera F, Villar P (2001) Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base. IEEE Trans Fuzzy Systems 9(4):667–674

    Article  Google Scholar 

  21. Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int Journal on ManMachine Studies 7(1):1–13

    Article  MATH  Google Scholar 

  22. Kumar D, Pon DN, Murugesan K (2012) Performance analysis of neural networks based priority scheduler for WiMAX under bursty traffic conditions. Journal of Scientific Research 76(3):351–365

    Google Scholar 

  23. McEachen J C, Zachary J M. Real-time representation of network traffic behavior for enhanced security. In Proc. the 3rd ICITA, July 2005, pp.214–219.

  24. García-Galán S, Prado RP, Expósito JEM (2012) Fuzzy scheduling with swarm intelligence-based knowledge acquisition for grid computing. Engineering Applications of Artificial Intelligence 25(2):359–375

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chollette C. Chude-Olisah.

Additional information

This work was supported by the Ministry of Science and Teknologi Malaysia eScience under Grant No. 4S034 managed by Research Management Centre of Universiti Teknologi Malaysia.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

(DOC 24.9 KB)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chude-Olisah, C.C., Chude-Okonkwo, U.A.K., Bakar, K.A. et al. Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks. J. Comput. Sci. Technol. 28, 357–365 (2013). https://doi.org/10.1007/s11390-013-1336-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11390-013-1336-2

Keywords

Navigation