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Numerical results show that the tiered service based on virtual networks can be more profitable than the non-tiered service under proper pricing and capacity partitioning.
While the initial capacity partitioning guarantees a reliable operation for the worst-case scenario, at the same time it could lead to capacity underutilization under normal traffic conditions.
The first module is an Integrated SAC ISACC) frontend, which is based on the effectiveness of the well-known capacity partitioning rationale, while it is complemented with a novel periodic partition adjustment (PPA) process that addresses any backhaul capacity fluctuations as well as variations of traffic load composition.
Then, we find the optimal pricing and capacity partitioning by addressing the revenue maximization problem in the tiered service.
Consequently, the initial virtual capacity partitioning should be performed for the worst-case situation, where the traffic load intensity A j offered by each ISG j has its maximum value, while at the same time the backhaul capacity has its minimum value Cmin.
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As long as the virtual capacity partitions are defined, the admission decision process, as shown at Figure 4, is straightforward.
At the same time, the reduced streaming video traffic makes use of a capacity partition that is initially designed to handle a significantly higher traffic volume.
As a result, the proposed CA-FEI scheme is more flexible compared to typical one-tier schemes that utilize actual capacity partitions and thus it is able to achieve higher utilization of the backhaul capacity.
Both CA-FEI and HPS schemes arrange their capacity partitions expecting at the worst case a 35% reduction of the backhaul capacity as well as a traffic load distribution consisting of only delay sensitive services (40% Voice, 30% Video-telephony, and 30% Streaming video) all having a target GoS of 1%.
If this is the case, then the relay module can inform CIAM about the wireless backhaul link alternative and consequently the CIAM will update the wired backhaul capacity partitions (i.e., PPA process described in Section 4), so that the latter can be restructured in favor of the QoS/QoE metrics for UEs.
The capacity to partition natural, indirect, and direct human-induced effects on terrestrial carbon (C) sources and sinks is necessary to be able to predict future terrestrial C dynamics and thus their influence on atmospheric CO2 growth.
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