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QoS Assessment over Multiple Attributes

QoS Assessment over Multiple Attributes,10.1109/CIT.2010.260,Hmood Al-Dossari,Jianhua Shao,Alun D. Preece

QoS Assessment over Multiple Attributes   (Citations: 1)
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In an open service oriented computing environment, multiple providers may offer functionally identical services but with varying qualities. It is desirable therefore that we are able to assess the quality of a service (QoS), so that service consumers can be given additional guidance in selecting their preferred services. Various methods have been proposed to assess QoS using the data collected from monitoring tools, but they do not deal with multiple QoS attributes adequately. Typically these methods assume that the quality of a service may be assessed by first assessing the quality level delivered by each QoS attribute individually, and then aggregating them in some way to give an overall verdict for the service. In this paper, we show that this may lead to incorrect assessment, and suggest how existing methods may be improved to deal with multiple attributes more effectively.
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    • ...Suppose that we have a set of QoS data collected for service S that has two attributes A1 and A2, and the collected data is shown in Table I. For simplicity of discussion we assume that QoS data is normalised to a value in [0;1] in this paper...
    • ...One possible solution to this problem is to assess QoS per user expectation [1], [13]...
    • ...When QoS data across multiple attributes is not synchronously collected, the approach suggested in [1], [13] could have substantially less data to use...
    • ...where d(Ai) and e(Ai) are normalised values in [0;1] 1 , with 0 representing the minimum level of quality and 1 the maximum...
    • ...So the ratio of and will determine where in the interval [0,1] the distribution peaks, and a high will cause the distribution mode to occur close to 1...
    • ...by considering the synchronous subset only [1], the amount of available data for assessment may be significantly reduced, particularly when the dimensionality is high...
    • ...We compare 4 methods: the Averaging All (AA) approach [8], [21] which averages all the data in each attribute separately and then aggregate them as a weighted average; the Multiple Quality-Space Mapping (MQSM) method [13] which also processes each attribute separately, but attempts to identify possible quality packages within a single attribute; the Synchronous Only extension (SE) to MQSM [1] which is capable of identifying quality ...
    • ...In [1], this approach was extended to deal with quality packages that may exist across multiple attributes...

    Hmood Al-Dossariet al. Handling asynchronous data in assessing QoS over multiple attributes

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