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    A Novel Wavelet-Based Approach to Enhance the Performance of Mobile-Business Systems

    152179_152179.pdf (669.1Kb)
    Access Status
    Open access
    Authors
    Lin, W.
    Wong, A.
    Dillon, Tharam S.
    Chang, Elizabeth
    Date
    2010
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Lin, Wilfred W.K. and Wong, Allan K.Y. and Dillon, Tharam S. and Chang, Elizabeth. 2010. A Novel Wavelet-Based Approach to Enhance the Performance of Mobile-Business Systems, in Ismail, L. and Chang, E. and Karduck, A.P. (ed), IEEE international conference on digital ecosystems and technologies (DEST 2010), Apr 12 2010, pp. 112-117. Dubai, United Arab Emirates: IEEE.
    Source Title
    Proceedings of the IEEE international conference on digital ecosystems and technologies (DEST 2010)
    Source Conference
    IEEE international conference on digital ecosystems and technologies (DEST 2010)
    DOI
    10.1109/DEST.2010.5610660
    ISBN
    9781424455515
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    Remarks

    Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/3166
    Collection
    • Curtin Research Publications
    Abstract

    We propose a novel wavelet-based approach (WBA) that accurately decides if the Internet traffic is currently SRD (short-range dependence) or LRD (long-range dependence) on the fly. As a result, it helps a real-time dynamic cache size tuner such as the MACSC (Model for Adaptive Cache Size Control) maintain the given cache hit ratio under all Internet traffic conditions. The WBA mechanism utilizes the following unique characteristics of wavelet coefficients (WC) for stationary signals f(x) : i) WC values by discrete wavelet transform (DWT), irrespective to if f(x) is SRD or LRD, are always SRD; ii) if f(x) is LRD then the WC variances scale divergently with the dilation factor; and iii) WC variances of SRD signals, however, converge to a constant. The DWT process is Dj,k = (f(x) , (J)j,k) or += Tji2 f f(x)w(Tj X - k)dx formally, where Dj,k arethe WC values, (J)j.k the mother wavelet, j the dilation factor/scale, and k the translation factor.

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