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As the proposed method is focused on temporary congestion situations and prioritize voice traffic, the algorithm must evaluate the network indicators in short periods.
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In short, for exponential traffic, the algorithms are successful when they identify an attack, but they cannot identify the majority of attacks, leading to a huge number of false negatives.
We also incorporate three different classes of traffic into the algorithm.
As can be observed, as the traffic decreases, the algorithm tends to switch off more macro-cells and activate the micro-cells in the targeted area.
Based on the information in the requested traffic trunk, the algorithm tries to locate LSP using shortest path through a sub-graph that best meets the request [4].
Should the outliers be deemed to represent more than 0.3% of the total traffic, then the algorithm considers that there may be a change in the average and increases the outlier bounds to accommodate this new traffic.
Section 'Evaluation of overhead traffic' investigates the overhead traffic generated by the algorithm.
The amount of overhead traffic generated by the algorithm can be evaluated.
Examiner CEO Rick Blair says the site's traffic fluctuates and the algorithm change "has enhanced the visibility of some of our best and most appealing content".
In experiment 1 with only TCP traffic, the proposed marker algorithm studied the performance of fairness behaviour for the different marker algorithms for three different scenarios.
Since a fixed subframe split ratio of DL/UL may cause DL or UL to be overloaded when diverse multimedia service traffics are severe, the algorithm adjusting dynamically the DL/UL ratio based on the amount of the DL data queues and the UL request queues is needed to be employed, as explained as follows.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com