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A simulation model, consisting of two homogeneous clusters, is considered to evaluate the performance for various workloads.
We evaluate the performance for three input spaces consisting of the power spectral density, byte probability distribution and sliding-window entropy of the byte sequence in a file.
To evaluate the performance for different reverberation, simulated data was used.
To evaluate the performance for inter CDC for cloud federation, Cerroni [92] presented a model.
However, to evaluate the performance for all classes was used the micro-average and macro-average metrics [20].
Furthermore, another spambase dataset obtained from UCI repository is used to evaluate the performance for the proposed ABBDT approach [36].
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In this section, we evaluate the performance of POCS for non-cooperative and cooperative networks.
We evaluate the performance of LETX for NST-AODV in this paper.
We chose two measures to evaluate the performance of algorithms for selecting the best individuals.
We also evaluate the performance of SSR for reducing extracerebral contribution.
Two kinds of criteria are used in the paper to evaluate the performance of algorithms for identifying protein complexes.
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