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In addition to the maps, times of peak ground motion at sources were interpolated from real seismological data.
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Figure 21 shows the results for the mapping times of the algorithms on a logarithmic scale.
Moreover, Figure 26 shows the results for the mapping times of the algorithms.
The reconfiguration time of a single node is negligible compared to the download and mapping times of a Pervasive App.
The adopted values in this experiment were chosen empirically with the aim of reducing the mapping times of the algorithms.
We used a logarithmic scale for charts showing mapping times of the algorithms, thereby providing better visualization and comparison of the results.
Figures 23 and 24 show the results obtained for these datasets, in terms of delta sizes and mapping times of the algorithms, respectively.
Compared with A p p r o x M a p 5/25%, the mapping times of A l g Hung increased by between 0.11 and 1.92.
Compared with A l g Sign, the increase in mapping times of A p p r o x M a p 5/25% varied between 0.46 and 1.59.
In the final three instances, Alg Sign achieved better performance than ApproxMap 5/25%, with decreased mapping time of between 0.12 and 0.65.
Map phase execution time can be calculated by Eq. (5), where the average processing time of input data block in each wave multiplied by the corresponding number of wave is the map time of the ith data center.
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