2006
DOI: 10.1007/11814856_9
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A New Methodology of QoS Evaluation and Service Selection for Ubiquitous Computing

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Cited by 14 publications
(19 citation statements)
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“…3. This was inspired by the work of [3], [4], in which the authors used sigmf and gaussmf membership functions to map various parameters, such as the network's bandwidth and latency, to quality values between 0 and 1. By varying the values of α and β, it is possible to create a family of curves that have the same behavior.…”
Section: Transport Quality Evaluationmentioning
confidence: 99%
“…3. This was inspired by the work of [3], [4], in which the authors used sigmf and gaussmf membership functions to map various parameters, such as the network's bandwidth and latency, to quality values between 0 and 1. By varying the values of α and β, it is possible to create a family of curves that have the same behavior.…”
Section: Transport Quality Evaluationmentioning
confidence: 99%
“…In the area of static content adaptation different versions of the original content are created and stored on a server [24,22,20,11,34]. At runtime, when the content is requested, the optimal version, evaluated using a specific quality criterion, is selected for delivery.…”
Section: Static and Dynamic Adaptationmentioning
confidence: 99%
“…We therefore propose to evaluate transport quality using a normalization Z-shaped built-in membership function (Zmf) [31]. This was inspired by the work of [20,34], in which the authors used the sigmf and gaussmf membership functions to normalize various parameters, such as the network bandwidth and latency. This function, (Zmf), expresses the end-user's appreciation of (or frustration with) the adapted content, as a function of the wait time, in terms of a behavior.…”
Section: Transport Quality Evaluationmentioning
confidence: 99%
“…For example, Liu and Jin propose fuzzy analytic hierarchy process to define the weight factor of QoS [9]. Zhang et al design a user preference model based on linguistic variable and apply a hierarchical fuzzy logic evaluation [10]. Chen et al adopt Fuzzy Multiple Criteria Decision Making (FMCDM) approach to capture how customers make their evaluation of services more effectively [11].…”
Section: Introductionmentioning
confidence: 99%
“…Mon applies entropy weight to model objective significance of the criteria by fuzzy analytic hierarchy process [13]. These studies [3][4][5][6][7][8][9][10][11][12][13] motivate the research work presented in this paper.…”
Section: Introductionmentioning
confidence: 99%