An adaptive statistical sampling technique for computer network traffic

DOGMAN, A., SAATCHI, R. and AL-KHAYATT, S. (2010). An adaptive statistical sampling technique for computer network traffic. In: GHASSEMLOOY, Zabih and NG, Wai Pang, (eds.) Proceeding of the seventh, IEEE, IET international symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). Newcastle, Northumbria University, 479-483.

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    The rapid growth of real-time applications transmitted over multimedia networks, makes measurement of their generated traffic increasingly important. These measurements allow the quality of service (QoS) provided by the network for the transmission of the applications to be assessed. However, most real-time applications generate an extensive amount of traffic data. Analysing these data in real-time is computationally intensive. Therefore, in order to reduce the amount of processed data, sampling needs to be performed. In fixed rate sampling, the sample rate is unaffected by the packet transmission rate. However, it is advantageous to adapt the sample rate in relation to packet transmission rate. In this study a novel statistical adaptive sampling method has been developed. The method adaptively adjusts the time interval between two consecutive sampled sections (called pre-and post sampling sections). This time interval is decreased when the two sections significantly differ statistically and it is increased when their net statistic is within a predefined threshold. The operation of the developed sampling method was evaluated using a simulated computer network. The results demonstrated the effectiveness of the method in various scenarios, however more work is in progress to make the method more robust.

    Item Type: Book Section
    Additional Information: 21-23 July 2010, Northumbria University, Newcastle upon Tyne Institution of
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Page Range: 479-483
    Depositing User: Ann Betterton
    Date Deposited: 13 Dec 2010 11:59
    Last Modified: 18 Mar 2021 09:00

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