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We executed algorithm (15) with α : = 9 / 10 and algorithm (15) with α : = 1 / 2 for these initial points.

The lemma states that there is "some task ready to be executed,"—which means there are at least two tuples in the space (T is the taskId and J is its jobId): The lemma also states that there is a resource r that can execute T and is correct, i.e., executed Algorithm 2 forever without stopping.

While the fully executed algorithm is potentially useful, in practice it is not practical due to its computational complexity.

The approach we take is to analytically mimic the function of the fully executed algorithm that generates the networks, which are samples of G ens.

Comparison of running times between the fully executed algorithm and the approximation is shown in Figure 7Figure 7; this shows that the analytical approximation is two orders of magnitude faster than algorithmic sampling and therefore more practical for generating networks from real datasets stored as GMT files.

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After executing Algorithm 2, we have got a subtree over on S1∪C.

If channel n belongs to N1, execute Algorithm 5 to do bandwidth rescheduling.

On executing Algorithm 6, first the optimum bandwidth is obtained with the corresponding power allocation.

Nodes in S r (t), which are in hexagon 8, execute Algorithm 3 in frame (mathcal {F}_{8}).

In this paper, the problem is nonuniform antenna design, which should be preset ahead of executing algorithm.

The algorithm alternately executes Algorithm 2, to obtain network configurations with low energy consumption, and updates the link spectral efficiency ω by a fixed point algorithm.

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