## 5 Numerical Results and Performance Analysis
### Numerical Results  
#### 5.2.1 Transport Network Latency  
We first analyze the transport network latency when allocating resources over s-VCC slices, eRTC slices and eMBB slices concurrently. There are two simulation environments, uniform and non-uniform VNU capacity in substrate nodes, as shown in Table 2. The VNU capacity indicates the number of VNUUs that a substrate network node can accommodate. Under the uniform VNU capacity condition, Figure 3(a) compares the transport network latency among three type slices and the latency threshold which depends on the class of services. We can notice our model provides an excellent latency for all NSIs without exceeding the required latency threshold.  
The assumption of uniform VNU capacity can be ideal sometimes, since the VNU availability in substrate networks is time-varying. The reasons can be, for instance, the time-varying switch port/interface failures [51]. Consequently, in Figure 3(b), we evaluate the same transport network latency under the non-uniform VNU capacity, which gradually decreases in the core, aggregation and access layer networks. As expected, the ultra-low latency requirement of latency-sensitive slices, including s-VCC slices and eRTC slices, is satisfied as well, while the latency increases slightly comparing to Figure 3(a). It also proved that minimizing the backhaul transport latency is necessary for preventing the extreme service requirements from deteriorating due to time-varying network and unexpected traffic.  
The network capacity in three-layer networks is different: the link capacity can be lower in the access layer network, and higher as moving into the core layer network. In this regard, we change the connectivity of substrate nodes in access layer network from 5% to 60% to analyze the transport network latency over three types of service-oriented slices. Changing network node connectivity will  
Figure 4: Transport network latency for different network slices when the VNU capacity of DCs is uniform and non-uniform.  
Figure 3: Example of the backhaul transport network in a simulation timestamp.  
increase/decrease network capacity in the access layer network, aiming to simulate time-varying and deteriorating network scenarios. In Figure 5, we can observe that the latency of both types of latency-sensitive slices reduce significantly with node connectivity due to increasing access layer network resources. This outcome shows that the provisioning of ultra-low latency demands largely relies on the allocating edge DCs' resources. Or other, unnecessary latency is mainly generated by redundant path allocation if the target rate can be provided, conforming to our design principles.  
To obviously evaluate the latency, we use the proposed scheme, NSDP scheme and RFPA scheme to deploy three type slices concurrently. Figure 6 compares the transport network latency with the increased number of slices. We observe a latency reduction in our model of up to 30.01% and 41.63% compared to the NSDP and RFPA respectively. As a result, our model provides a minimal transport network latency, which is far lower than others and increases slowly with the amount of concurrent NSIs. Such result is that our model tries to balance the link load in access, aggregation and core layer networks, so that edge DCs' resources are reserved to latency-sensitive NSIs as much as possible for transmission distance reduction. In addition, other approaches disregard the low transmission rate generated by poor link capacity provided to the massive traffic of eMBB.