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In the future, this restriction might be removed as a recent report has described the development of TALE frameworks that demonstrate no base restrictions at this position and allow for any sequence to be targeted.
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Then, we investigate whether the TaLE framework can be immune to the mobility.
Conclusively, the TaLE framework supports per-location service differentiation and fairness efficiently.
Firstly, we evaluate the TaLE framework with respect to per-location throughput.
As for the computational complexity of the proposed TaLE framework, we have the following investigation results.
As the next performance study, we investigate the effect of station mobility on the TaLE framework.
The details on how to use and estimate per-location target load in TaLE will be accounted for in what follows, and also the overall TaLE framework is demonstrated in Figure 3. Figure 3 TaLE framework.
Figure 13 compares the network-wide aggregate throughput and loss rate between IEEE 802.11-based and the TaLE framework.
In Figure 9, we can perceive that the TaLE framework provides distinct service differentiation agreeable to given weights.
In order to verify that the TaLE framework achieves more elaborate service differentiation, we carry out an additional simulation study.
Then, we evaluate the TaLE framework in perspective of the network-wide aggregate throughput and frame loss rate.
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