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    Detection and Mitigation of Impairments for Real-Time Multimedia Applications

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    Issue Date
    2007-12-14
    Author
    Bali, Soshant
    Publisher
    University of Kansas
    Format
    188 pages
    Type
    Dissertation
    Degree Level
    PH.D.
    Discipline
    Electrical Engineering & Computer Science
    Rights
    This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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    Abstract
    Measures of Quality of Service (QoS) for multimedia services should focus on phenomena that are observable to the end-user. Metrics such as delay and loss may have little direct meaning to the end-user because knowledge of specific coding and/or adaptive techniques is required to translate delay and loss to the user-perceived performance. Impairment events, as defined in this dissertation, are observable by the end-users independent of coding, adaptive playout or packet loss concealment techniques employed by their multimedia applications. Methods for detecting real-time multimedia (RTM) impairment events from end-to-end measurements are developed here and evaluated using 26 days of PlanetLab measurements collected over nine different Internet paths. Furthermore, methods for detecting impairment-causing network events like route changes and congestion are also developed. The advanced detection techniques developed in this work can be used by applications to detect and match response to network events. The heuristics-based techniques for detecting congestion and route changes were evaluated using PlanetLab measurements. It was found that Congestion events occurred for 6-8 hours during the days on weekdays on two paths. The heuristics-based route change detection algorithm detected 71\% of the visible layer 2 route changes and did not detect the events that occurred too close together in time or the events for which the minimum RTT change was small. A practical model-based route change detector named the parameter unaware detector (PUD) is also developed in this deissertation because it was expected that model-based detectors would perform better than the heuristics-based detector. Also, the optimal detector named the parameter aware detector (PAD) is developed and is useful because it provides the upper bound on the performance of any detector. The analysis for predicting the performance of PAD is another important contribution of this work. Simulation results prove that the model-based PUD algorithm has acceptable performance over a larger region of the parameter space than the heuristics-based algorithm and this difference in performance increases with an increase in the window size. Also, it is shown that both practical algorithms have a smaller acceptable performance region compared to the optimal algorithm. The model-based algorithms proposed in this dissertation are based on the assumption that RTTs have a Gamma density function. This Gamma distribution assumption may not hold when there are wireless links in the path. A study of CDMA 1xEVDO networks was initiated to understand the delay characteristics of these networks. During this study, it was found that the widely deployed proportional-fair (PF) scheduler can be corrupted accidentally or deliberately to cause RTM impairments. This is demonstrated using measurements conducted over both in-lab and deployed CDMA 1xEVDO networks. A new variant to PF that solves the impairment vulnerability of the PF algorithm is proposed and evaluated using ns-2 simulations. It is shown that this new scheduler solution together with a new adaptive-alpha initialization stratergy reduces the starvation problem of the PF algorithm.
    URI
    http://hdl.handle.net/1808/1979
    Collections
    • Dissertations [4474]
    • Engineering Dissertations and Theses [1055]

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    KU Libraries
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    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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