overing a request of all the algorithms increases drastically. This is because in the 10 Robust RAN Slicing ROBUST with 10% tolerance VNS with 30% tolerance VNS with 10% tolerance ROBUST with 30% tolerance ROBUST with 10% tolerance VNS with 10% tolerance ROBUST with 30% tolerance VNS with 30% tolerance Figure 10.5 The relationship between failure rate of requests and average load of substrate links. (a) Variation of RF with fixed U1 and (b) variation of U, with fixed RF. beginning of simulation, small amounts of failure occur in substrate nodes and links, which results in enough residual substrate resources to enable successful recoveries by ROBUST and VNS, while near the end of the simulation, in which almost all the substrate nodes and links are failed, it becomes difficult for either ROBUST or VNS to find a feasible solution. As expected, we can observe that ROBUST with 30% tolerance of link uncertainty requires the longest time compared with the rest of the curves, while VNS with 10% tolerance of link uncertainty requires the least time compared with the rest of the curves. Owing to 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 10.6 Average time of recovering a request over time. (a) Medium uncertainty scenario and (b) high uncertainty scenario. this, ROBUST with 30% tolerance needs more computation time for an optimal solution compared with ROBUST with 10% tolerance and VNS. In contrast, VNS with 10% tolerance needs much less time to converge for a sub-optimal solution. This fact reveals that there is also a trade-off between the robustness of a request and the time consumption for request recovery. 10 Robust RAN Slicing Conclusions and Future Work Network slicing has become one of the most discussed capabilities of 5G to provide multiple end-to-end networks with logical isolation for the