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Cited by 7 publications
(3 citation statements)
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“…In (Mieghem, 1999) the parameters that can be aggregated, are distinguished into three classes: additive, min-max and the combination of additive and min-max metrics (multi-criteria). Topology aggregation based on such metrics is investigated in (Bauer et al, 2006), considering only network-related parameters (namely, delay and bandwidth). In the same context (Bauer et al, 2006) presents a topology aggregation scheme that is subject to multi-criteria (delay and bandwidth) constraints.…”
Section: Previous Workmentioning
confidence: 99%
See 1 more Smart Citation
“…In (Mieghem, 1999) the parameters that can be aggregated, are distinguished into three classes: additive, min-max and the combination of additive and min-max metrics (multi-criteria). Topology aggregation based on such metrics is investigated in (Bauer et al, 2006), considering only network-related parameters (namely, delay and bandwidth). In the same context (Bauer et al, 2006) presents a topology aggregation scheme that is subject to multi-criteria (delay and bandwidth) constraints.…”
Section: Previous Workmentioning
confidence: 99%
“…Topology aggregation based on such metrics is investigated in (Bauer et al, 2006), considering only network-related parameters (namely, delay and bandwidth). In the same context (Bauer et al, 2006) presents a topology aggregation scheme that is subject to multi-criteria (delay and bandwidth) constraints. Specifically, a transition matrix is constructed containing the minimum information that describes exactly the traversing characteristics of a domain, that is, the characteristics of the paths connecting border (ingress-egress) node pairs of the domain.…”
Section: Previous Workmentioning
confidence: 99%
“…The set of representative points (convex corner points) form a nondescending staircase, or efficient frontier [12], we call it S. In the worst circumstance, there may be |E| representative points on S. In order to reduce the space complexity, we should keep a constant number of points to represent S. Fig.2, the basic idea of our method is using linear regression to find a curve fitting that represents all representatives. Linear regression is a form of regression analysis in which data are modeled by a least squares function which is a linear combination of the model parameters and depends on one or more independent variables.…”
Section: A Full Mesh Constructionmentioning
confidence: 99%