Embedded fuzzy expert system for Adaptive Weighted Fair Queueing

Tapio Frantti, Mirjami Jutila

    Research output: Contribution to journalArticleScientificpeer-review

    8 Citations (Scopus)

    Abstract

    This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.
    Original languageEnglish
    Pages (from-to)11390-11397
    Number of pages8
    JournalExpert Systems with Applications
    Volume36
    Issue number8
    DOIs
    Publication statusPublished - 2009
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Expert systems
    Quality of service
    Scheduling
    Routers
    Telecommunication traffic
    Internet
    Bandwidth

    Keywords

    • Adaptive WFQ
    • Fuzzy reasoning
    • QoS
    • Scheduling
    • Embedded expert system

    Cite this

    Frantti, Tapio ; Jutila, Mirjami. / Embedded fuzzy expert system for Adaptive Weighted Fair Queueing. In: Expert Systems with Applications. 2009 ; Vol. 36, No. 8. pp. 11390-11397.
    @article{081216b91d704b42848c6ef4ea15d898,
    title = "Embedded fuzzy expert system for Adaptive Weighted Fair Queueing",
    abstract = "This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.",
    keywords = "Adaptive WFQ, Fuzzy reasoning, QoS, Scheduling, Embedded expert system",
    author = "Tapio Frantti and Mirjami Jutila",
    year = "2009",
    doi = "10.1016/j.eswa.2009.03.038",
    language = "English",
    volume = "36",
    pages = "11390--11397",
    journal = "Expert Systems with Applications",
    issn = "0957-4174",
    publisher = "Elsevier",
    number = "8",

    }

    Embedded fuzzy expert system for Adaptive Weighted Fair Queueing. / Frantti, Tapio; Jutila, Mirjami.

    In: Expert Systems with Applications, Vol. 36, No. 8, 2009, p. 11390-11397.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Embedded fuzzy expert system for Adaptive Weighted Fair Queueing

    AU - Frantti, Tapio

    AU - Jutila, Mirjami

    PY - 2009

    Y1 - 2009

    N2 - This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.

    AB - This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.

    KW - Adaptive WFQ

    KW - Fuzzy reasoning

    KW - QoS

    KW - Scheduling

    KW - Embedded expert system

    U2 - 10.1016/j.eswa.2009.03.038

    DO - 10.1016/j.eswa.2009.03.038

    M3 - Article

    VL - 36

    SP - 11390

    EP - 11397

    JO - Expert Systems with Applications

    JF - Expert Systems with Applications

    SN - 0957-4174

    IS - 8

    ER -