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Depending on the job load some resources become critical and may become performance bottleneck [32, 33].
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Due to signaling management and packets delivery, the mobile router may become the performance bottleneck and single point failure by the malicious attack.
In strong scaling scenarios for highly clustered datasets, domain decomposition may become a performance bottleneck, as the number of splitters generally depends on the number of processors used in the run.
Actors become performance artists.
It may become a major performance bottleneck of a C-RAN system per critical indicators such as spectral efficiency and latency [1 3].
In case that the computation on an individual vertex is extremely time-consuming due to the large number of maximal cliques, it may become a parallel performance bottleneck.
Most of the state-of-the-art techniques that reduce the energy consumption of directories are at the cost of performance, which may become unacceptable for high-performance CMPs.
Their performance may become extremely bad when the second threshold is improperly chosen.
This performance may become much worse when the training samples are imbalanced.
However, the tracking performance may become very poor if the actual plant parameters deviate too much from the nominal ones.
In a resource limited and competed environment, these resource-hungry algorithms should not be used, otherwise the whole system performance may become even worse [25, 26].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com