Why "plain" DEA isn't enough
The Hurst parameter and fractal dimension are ratio-form variables. Classical DEA models (CCR/BCC) violate convexity, proportionality and monotonicity when evaluating this kind of variable, producing incorrect efficiency frontiers. That's why each stage of the research proposed a multiplicative variant — with a logarithmic transformation — suited to this problem.
The same three variables, across every model
Fractal Dimension (D)
Measures traffic smoothness/irregularity. Ranges from 1 to 2: the closer to 1, the more stable; the closer to 2, the more irregular and bursty.
Hurst Parameter (H)
Measures the series' time memory. H > 0.5 indicates long-range dependence (the pattern tends to repeat in the future) — only series with H > 0.5 are useful for prediction.
Average TCP Throughput
Average bandwidth measured by iperf/iperf3 across each configuration's (DMU) time series.
Three concrete advantages over CCR and BCC
From classical DEA to Super-Cobb-Douglas
Advantages and limitations, side by side
| Model | Orientation / mechanics | Advantage | Limitation |
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