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Volume 28 Issue 2
March  2013
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Chollette C. Chude-Olisah, Uche A. K. Chude-Okonkwo, Kamalrulnizam A. Bakar, Ghazali Sulong. Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks[J]. Journal of Computer Science and Technology, 2013, 28(2): 357-365. DOI: 10.1007/s11390-013-1336-2
Citation: Chollette C. Chude-Olisah, Uche A. K. Chude-Okonkwo, Kamalrulnizam A. Bakar, Ghazali Sulong. Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks[J]. Journal of Computer Science and Technology, 2013, 28(2): 357-365. DOI: 10.1007/s11390-013-1336-2
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Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks

  • 1 Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru 81110, Malaysia;
    2 Wireless Communication Center, Universiti Teknologi Malaysia, Johor Bahru 81110, Malaysia

Funds: 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.
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  • Received Date: November 01, 2011
  • Revised Date: January 08, 2013
  • Published Date: March 04, 2013
    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 in皍ences 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).
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    • References (24)
  • [1]
    Sheldon T. Encyclopedia of Networking and Telecom-munications (Network Professionals Library). USA:Osborne/McGraw-Hill Press, 2001.
    [2]
    Guo Z, Zeng H. Simulation and analysis of weighted fair queu-ing algorithms in OPNET. In Proc. ICCMS, Feb. 2009,pp.114-118.
    [3]
    Padjen R, Keefer L, Thurston S et al. Flannagan and MartinWalshaw. Cisco AVVID and IP Telephony Design & Imple-mentation.
    [4]
    Cho H, Fadali M, Lee H. Dynamic queue scheduling usingfuzzy systems for Internet routers. In Proc. the 14th IEEEInt. Conf. Fuzzy Systems, May 2005, pp.471-476.
    [5]
    Cho H, Fadali M, Lee J et al. Lyapunov-based fuzzy queuescheduling for Internet routers. Journal of Control, Automa-tion and Systems, 2007, 5(3): 317-323.
    [6]
    Bolin N, Lemin L. Novel fuzzy scheduling supporting qualityof 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 prio-rity scheduler for mobile ad hoc networks and performanceanalysis for various mobility models. In Proc. IEEE WCNC,March 2004, pp.1087-1092.
    [8]
    Kazemian H B. A fuzzy approach to MPEG video trans-mission in ATM networks. Fuzzy Sets and Systems, 2006,157(16): 2259-2272.
    [9]
    Bourenane M, Benhamamouch D, Hamadouch H. Inductiveapproach for QoS packet scheduling in dynamic networks. InProc. ICMCS, April 2009, pp.25-30.
    [10]
    Bellman R E, Zadeh L A. Decision-making in a fuzzy envi-ronment. Management Science, 1970, 17(4): 141-164.
    [11]
    Blake S, Black D, Carlson M et al. An architecture fordifferentiated 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 inthe next generation Internet architectures. In Proc. the 5thIEEE ISCC, July 2000, pp.773-778.
    [13]
    Kanhere S S, Sethu H. Fair, efficient and low-latency packetscheduling using nested deficit round robin. In Proc. IEEEWorkshop on High Performance Switching and Routing, May2001, pp.6-10.
    [14]
    Wakuda K, Kasahara S. A packet scheduling algorithm formaxmin fairness in multihop wireless LANs. Journal of Com-puter Communications, May 2009, pp.1437-1444.
    [15]
    Nagle J. On packet switches with infinite storage. IEEETrans. Communication, 1987, 35(4): 435-438.
    [16]
    Demers A, Keshav K, Shenker S. Analysis and simulation ofa fair queueing algorithm. Comput. Commun. Rev., 1989,19(4): 1-12.
    [17]
    Stiliadis D, Varma A. Efficient fair queuing algorithm forpacket-switched networks. IEEE Trans. Networking, 1998,6(2): 175-185.
    [18]
    Kesh S, Nerur S, Ramanujan S. Quality of service | Tech-nology and implementation. Journal of Information Manage-ment & Computer Security, 2002, 10(2): 85-91.
    [19]
    Zadeh L A. Similarity relations and fuzzy orderings. Infor-mation Sciences, 1971, 3(2): 177-200.
    [20]
    Cordon O, Herrera F, Villar P. Generating the knowledge baseof a fuzzy rule-based system by the genetic learning of thedata base. IEEE Trans. Fuzzy Systems, 2001, 9(4): 667-674.
    [21]
    Mamdani E H, Assilian S. An experiment in linguistic syn-thesis with a fuzzy logic controller. Int. Journal on Man-Machine Studies, 1975, 7(1): 1-13.
    [22]
    Kumar D, Pon D N, Murugesan K. Performance analysis ofneural networks based priority scheduler for WiMAX underbursty traffic conditions. Journal of Scientific Research, 2012,76(3): 351-365.
    [23]
    McEachen J C, Zachary J M. Real-time representation of net-work traffic behavior for enhanced security. In Proc. the 3rdICITA, July 2005, pp.214-219.
    [24]
    García-Galán S, Prado R P, Expósito J E M. Fuzzy schedul-ing with swarm intelligence-based knowledge acquisition forgrid computing. Engineering Applications of Artificial Intel-ligence, 2012, 25(2): 359-375.
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