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(In fact, for large networks it can be extremely difficult to follow exactly how an output was determined).
Furthermore, the scheme is not scalable for large networks.
Distributed algorithms are scalable and thus attractive for large networks.
This may not be possible for large networks.
A heuristic method is presented for large networks.
Traditional clustering algorithms often exhibit poor performance for large networks.
We can work on scaling these technologies, making them reliable for large networks.
Centralized algorithms are usually not scalable and thus impractical for large networks.
Tables 1 and 3 indicate the complexity of the analysis of JNCC for large networks.
Both algorithms are sensitive to the network size and, therefore, slower for large networks.
Therefore, for large networks, k1 and k2 could be considered as s and l approximately.
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CEO of Professional Science Editing for Scientists @ prosciediting.com