d 20%, respectively. We can observe that RF of ROBUST and VNS increases with the increase in U. Larger UL results in fewer substrate link resources left for RAN slices recovery, which in turn leads to higher RF. Similarly, we compare U S of ROBUST and VNS while fixing RF at the value of 5%, 10%, and 15%, respectively. We can observe that U S of ROBUST and VNS increases with the increase of RF. RF of ROBUST (resp. VNS) with 30% tolerance is smaller than that of ROBUST (resp. VNS) with 10% tolerance. Therefore, more redundancies intro- duced can result in higher robustness of RAN slices against link perturbations. From the results obtained SO far, we can see that there is a trade-off between RF (which reflects the robustness of a request) and U (which reflects how much resource that a request recovery needs to consume). For ease of comparison, we introduce the same redundancies in RAN slices of mMTC, eMBB, and URLLC. However, it should be noted that for slices with crit- ical requirements on reliability (e.g. URLLC slices), we can further promote its tolerance of link uncertainties by slightly sacrificing the link resource utilization, to ensure that the RAN slices are service-specific. 10.4 Numerical Results ROBUST with 10% tolerance ROBUST with 30% tolerance VNS with 10% tolerance VNS with 30% tolerance Simulation time (min) ROBUST with 10% tolerance ROBUST with 30% tolerance VNS with 10% tolerance VNS with 30% tolerance Simulation time (min) Figure 10.4 Average load of substrate links over time. (a) Medium uncertainty scenario and (b) high uncertainty scenario. In Figure 10.6a,b, we compare the average time of recovering a request by adopting the robust recovery algorithms under the high and medium uncertainty scenarios respectively. The curves of the average time of recovering a request in both scenarios have the same trend. In the beginning of simulation, the average time of recovering a request of all the algorithms increases slowly. However, when simulation time approaches 18 minutes, the average time of rec