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An Apache Hadoop cloud computing platform was implemented to reduce the computation time.
To reduce the computation cost, node i does not have to compute L is whenever N is is updated.
Parallel computing would be a promising strategy to reduce the computation time of the algorithm.
The block processing is applied to reduce the computation cost.
To reduce the computation complexity, correlation is used.
In order to reduce the computation time, the GSC can perform fragmentation-based shared spectrum allocation.
In order to reduce the computation quantities, we set (hbar_{f}=hbar_{g}=hbar_{theta}=hbar).
In NTSS, a halfway-stop technique is used to reduce the computation cost.
An approximate and simplified architecture is proposed to reduce the computation load.
A simplified implementing architecture is presented to reduce the computation load.
To reduce the computation time one can in principle do two things.
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