Embedded expert system for cognitive congestion and flow control in WLANs

Tapio Frantti, Mikko Majanen

    Research output: Chapter in Book/Report/Conference proceedingChapter or book articleProfessional

    Abstract

    This chapter introduces an embedded expert system for congestion and flow control of delay sensitive real-time traffic in Wireless Local Area Networks (WLANs). The expert system is based on the fuzzy set theory. It adjusts transceivers' traffic flow(s) for prevailing network conditions to achieve maximum throughput in required application dependent delay limits. In wireless networks delay and throughput are very much dependent on the packet size, packet transmission interval, and the node connection density. Therefore, the expert system on the destination node monitors congestion by measuring an average one-way delay and a change of one-way delay of the incoming traffic. Thereafter it adjusts packet size and transmission interval of the source node by transmitting a control command to the source. A linguistic decision making model of the expert system is described by linguistic relations. The linguistic relations form a rule base that is converted into numerical equations for transceiver's computational efficiency. The developed congestion and flow control method does packet size definition by at most 56 computations. In the system level, the feedback control increases only lightly communicational load by transmitting application level acknowledgements after every 200 received packets. The model was validated by simulating User Datagram Protocol (UDP) traffic in OMNeT++ network simulator. The achieved results demonstrate that the developed expert system is able to regulate packet sizes and transmission intervals to the prevailing application dependent optimum level very fast, accurately and with minimal overshoot and to increase overall throughput of the network. Even if this work is mainly motivated by the congestion and flow control of WLAN systems and the simulations and results were performed for the IEEE 802.11b system, the approach and the techniques are not limited to these systems, but are easily applicable for other Packet Switched Access Networks (PSANs), too.
    Original languageEnglish
    Title of host publicationExpert System Software
    Subtitle of host publication Engineering, Advantages and Applications
    EditorsJason M. Segura, Albert C. Reiter
    PublisherNova Science Publishers
    Chapter6
    Pages103-130
    ISBN (Print)978-1-61209-114-3
    Publication statusPublished - Jan 2013
    MoE publication typeD2 Article in professional manuals or guides or professional information systems or text book material

    Fingerprint

    Wireless local area networks (WLAN)
    Flow control
    Expert systems
    Linguistics
    Throughput
    Transceivers
    Fuzzy set theory
    Computational efficiency
    Feedback control
    Wireless networks
    Simulators
    Decision making
    Network protocols

    Keywords

    • expert systems
    • flow control
    • congestion control
    • packet size control
    • real-time traffic
    • PID
    • fuzzy control

    Cite this

    Frantti, T., & Majanen, M. (2013). Embedded expert system for cognitive congestion and flow control in WLANs. In J. M. Segura, & A. C. Reiter (Eds.), Expert System Software: Engineering, Advantages and Applications (pp. 103-130). Nova Science Publishers.
    Frantti, Tapio ; Majanen, Mikko. / Embedded expert system for cognitive congestion and flow control in WLANs. Expert System Software: Engineering, Advantages and Applications. editor / Jason M. Segura ; Albert C. Reiter. Nova Science Publishers, 2013. pp. 103-130
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    abstract = "This chapter introduces an embedded expert system for congestion and flow control of delay sensitive real-time traffic in Wireless Local Area Networks (WLANs). The expert system is based on the fuzzy set theory. It adjusts transceivers' traffic flow(s) for prevailing network conditions to achieve maximum throughput in required application dependent delay limits. In wireless networks delay and throughput are very much dependent on the packet size, packet transmission interval, and the node connection density. Therefore, the expert system on the destination node monitors congestion by measuring an average one-way delay and a change of one-way delay of the incoming traffic. Thereafter it adjusts packet size and transmission interval of the source node by transmitting a control command to the source. A linguistic decision making model of the expert system is described by linguistic relations. The linguistic relations form a rule base that is converted into numerical equations for transceiver's computational efficiency. The developed congestion and flow control method does packet size definition by at most 56 computations. In the system level, the feedback control increases only lightly communicational load by transmitting application level acknowledgements after every 200 received packets. The model was validated by simulating User Datagram Protocol (UDP) traffic in OMNeT++ network simulator. The achieved results demonstrate that the developed expert system is able to regulate packet sizes and transmission intervals to the prevailing application dependent optimum level very fast, accurately and with minimal overshoot and to increase overall throughput of the network. Even if this work is mainly motivated by the congestion and flow control of WLAN systems and the simulations and results were performed for the IEEE 802.11b system, the approach and the techniques are not limited to these systems, but are easily applicable for other Packet Switched Access Networks (PSANs), too.",
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    Frantti, T & Majanen, M 2013, Embedded expert system for cognitive congestion and flow control in WLANs. in JM Segura & AC Reiter (eds), Expert System Software: Engineering, Advantages and Applications. Nova Science Publishers, pp. 103-130.

    Embedded expert system for cognitive congestion and flow control in WLANs. / Frantti, Tapio; Majanen, Mikko.

    Expert System Software: Engineering, Advantages and Applications. ed. / Jason M. Segura; Albert C. Reiter. Nova Science Publishers, 2013. p. 103-130.

    Research output: Chapter in Book/Report/Conference proceedingChapter or book articleProfessional

    TY - CHAP

    T1 - Embedded expert system for cognitive congestion and flow control in WLANs

    AU - Frantti, Tapio

    AU - Majanen, Mikko

    N1 - Project code: 36036

    PY - 2013/1

    Y1 - 2013/1

    N2 - This chapter introduces an embedded expert system for congestion and flow control of delay sensitive real-time traffic in Wireless Local Area Networks (WLANs). The expert system is based on the fuzzy set theory. It adjusts transceivers' traffic flow(s) for prevailing network conditions to achieve maximum throughput in required application dependent delay limits. In wireless networks delay and throughput are very much dependent on the packet size, packet transmission interval, and the node connection density. Therefore, the expert system on the destination node monitors congestion by measuring an average one-way delay and a change of one-way delay of the incoming traffic. Thereafter it adjusts packet size and transmission interval of the source node by transmitting a control command to the source. A linguistic decision making model of the expert system is described by linguistic relations. The linguistic relations form a rule base that is converted into numerical equations for transceiver's computational efficiency. The developed congestion and flow control method does packet size definition by at most 56 computations. In the system level, the feedback control increases only lightly communicational load by transmitting application level acknowledgements after every 200 received packets. The model was validated by simulating User Datagram Protocol (UDP) traffic in OMNeT++ network simulator. The achieved results demonstrate that the developed expert system is able to regulate packet sizes and transmission intervals to the prevailing application dependent optimum level very fast, accurately and with minimal overshoot and to increase overall throughput of the network. Even if this work is mainly motivated by the congestion and flow control of WLAN systems and the simulations and results were performed for the IEEE 802.11b system, the approach and the techniques are not limited to these systems, but are easily applicable for other Packet Switched Access Networks (PSANs), too.

    AB - This chapter introduces an embedded expert system for congestion and flow control of delay sensitive real-time traffic in Wireless Local Area Networks (WLANs). The expert system is based on the fuzzy set theory. It adjusts transceivers' traffic flow(s) for prevailing network conditions to achieve maximum throughput in required application dependent delay limits. In wireless networks delay and throughput are very much dependent on the packet size, packet transmission interval, and the node connection density. Therefore, the expert system on the destination node monitors congestion by measuring an average one-way delay and a change of one-way delay of the incoming traffic. Thereafter it adjusts packet size and transmission interval of the source node by transmitting a control command to the source. A linguistic decision making model of the expert system is described by linguistic relations. The linguistic relations form a rule base that is converted into numerical equations for transceiver's computational efficiency. The developed congestion and flow control method does packet size definition by at most 56 computations. In the system level, the feedback control increases only lightly communicational load by transmitting application level acknowledgements after every 200 received packets. The model was validated by simulating User Datagram Protocol (UDP) traffic in OMNeT++ network simulator. The achieved results demonstrate that the developed expert system is able to regulate packet sizes and transmission intervals to the prevailing application dependent optimum level very fast, accurately and with minimal overshoot and to increase overall throughput of the network. Even if this work is mainly motivated by the congestion and flow control of WLAN systems and the simulations and results were performed for the IEEE 802.11b system, the approach and the techniques are not limited to these systems, but are easily applicable for other Packet Switched Access Networks (PSANs), too.

    KW - expert systems

    KW - flow control

    KW - congestion control

    KW - packet size control

    KW - real-time traffic

    KW - PID

    KW - fuzzy control

    M3 - Chapter or book article

    SN - 978-1-61209-114-3

    SP - 103

    EP - 130

    BT - Expert System Software

    A2 - Segura, Jason M.

    A2 - Reiter, Albert C.

    PB - Nova Science Publishers

    ER -

    Frantti T, Majanen M. Embedded expert system for cognitive congestion and flow control in WLANs. In Segura JM, Reiter AC, editors, Expert System Software: Engineering, Advantages and Applications. Nova Science Publishers. 2013. p. 103-130