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    Maximizing bandwidth using disjoint paths

    150212_150212.pdf (341.0Kb)
    Access Status
    Open access
    Authors
    Loh, R.
    Soh, Sieteng
    Lazarescu, Mihai
    Date
    2010
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Loh, R. and Soh, Sieteng and Lazarescu, Mihai. 2010. Maximizing bandwidth using disjoint paths, in Rahayu, W., Xhafa, F. & Denko, M. (ed), 2010 24th IEEE International Conference on Advanced Information Networking and Applications, Apr 20 2010, pp. 304-311. Perth, Western Australia: IEEE Computer Society.
    Source Title
    Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
    Source Conference
    2010 24th IEEE International Conference on Advanced Information Networking and Applications
    ISSN
    1550-445X
    Faculty
    School of Science and Computing
    Department of Computing
    Faculty of Science and Engineering
    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/20.500.11937/47475
    Collection
    • Curtin Research Publications
    Abstract

    Recently, multi-paths solutions have been proposed to improve the quality-of-service (QoS) in communication networks (CNs). This paper addresses the problem to obtain the λ-edge-disjoint-path-set (λDP/B) with maximum bandwidth (λDPB), for λ>/=1. λDP/B is useful for applications that require maximum bandwidth for data transmission, such as video conferencing, video-on-demand, large file downloads and FTP. We propose a polynomial time heuristic algorithm, Maximum Bandwidth Algorithm (MBA), to solve the problem. We have implemented MBA and evaluated its performance against an optimal, but exponential time, brute force algorithm (BF) and three existing heuristicalgorithms: Algorithm-1, CBA-G', DPSP'. Simulations on seventy CNs show that MBA is able to produce the optimal λDPB for about 99% of the time while using only 0.005% CPU time of BF. Our simulations also show that MBA issignificantly more effective than these existing algorithms while using competitive CPU time.

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