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For many realistic networks, the node state in complex networks rely intensively on the time and space in many circumstances.
Therefore, before modeling the complex system as more realistic networks, some fundamental principles need to be defined.
It remains influential today, and has been incorporated into the GENESIS software for programming neurally realistic networks (Bower and Beeman 1995).
In realistic networks, we can use this analysis to quantitatively identify the impact area in traffic impact analysis and traffic operations.
In realistic networks, the distances among BSs in homogeneous cellular network can be easily acquired, but the position of UEs may not be easily and accurately acquired.
After describing this model, we provide examples of its behaviour on realistic networks under various scenarios, corresponding to potential real-world uses or policy interventions.
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According to Fig. 24 a reachability increases when the threshold increases in realistic network conditions also.
In [54], the green routing algorithms are analyzed based on realistic network scenarios.
We analyze the performance of the proposed algorithms under realistic network model.
To go further with the analysis, we resort to realistic network simulations.
The performance comparison is done by simulating a more realistic network environment.
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