# Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic
## 3 Evaluation  
In this section, we present a C-RAN example and provide simulation and analytical TC probabilities for the f-MC-SC model together with the corresponding analytical TC probabilities results for the f-SC-SC model of [27]. The simulation values presented in this example are based on SIMSCRIPT III [55] and are the mean values of seven runs. In every run (which took around 3 min of simulation time in a computer of Intel(R) Core(TM) i5-2430M CPU @ 2.4 GHz and 4 GB RAM), two hundred million calls are generated while the initial 5% of them is not taken into consideration in the TC probabilities so as to have a warm-up period [56; 57]. In the C-RAN example, let \(W=6\) RRHs of \(C=10\) RRUs. Furthermore, let \(T=30\) CRUs. The \(w\)-th RRH (\(w=1,\dots,6\)) serves \(S_{w}\) service classes and let \(b_{w,s}=b^{c}_{w,s}=b^{r}_{w,s}\) be the RUs required by a service class \(s\) call (which is going to be serviced in the \(w\)-th RRH). To be more specific, the first RRH accommodates \(S_{1}=3\) service classes. First service class calls require \(b_{1,1}=1\) RU, second service class calls require \(b_{1,2}=2\) RUs while third service class calls require \(b_{1,3}=3\) RUs. On the same hand, the second RRH accommodates \(S_{2}=2\) service classes, with \(b_{2,1}=2\) RUs and \(b_{2,2}=3\) RUs. Similarly, the third RRH accommodates \(S_{3}=2\) service classes, with \(b_{3,1}=1\) RU and \(b_{3,2}=3\) RUs; the fourth RRH accommodates \(S_{4}=2\) service classes, with \(b_{4,1}=1\) RU and \(b_{4,2}=2\) RUs; the fifth RRH accommodates a single service class with \(b_{5,1}=2\) RUs; and the sixth RRH accommodates a service class with \(b_{6,1}=1\) RU. Regarding the number of finite sources (i.e., MUs) that generate traffic, we assume that \(N_{w,s}=10\). As far as the offered traffic-load is concerned, we initially consider that \(\alpha_{w,s}=\alpha_{w,s,\text{idle}}N_{w,s}=1\) erl for all service classes in all RRHs (which refers to point 1 in the x-axis of Figures 3-9). We evaluate the C-RAN, by calculating the TC probabilities for 31 steps, where a 0.2 offered traffic-load increase per step is considered. Because of this, in the last step (point 31 in the x-axis of Figures 3-9) we have \(\alpha_{w,s}=7\) erl. For comparison, we study the f-SC-SC model of [27] where calls require a single RU for their connection with the number of RRHs, as well as the radio and computational capacity (in RUs) are exactly the same with those given above. Furthermore, all RRHs have a finite population of MUs equal to \(N_{w}=10\). As the model of [27] is a single service class model, we should express, for every RRH, the offered traffic-load \(\alpha_{w}\). Because of this, we adopt a load factor \(l_{w}\), expressed via \(l_{w}=\sum_{s=1}^{S_{w}}b_{w,s}\) where \(S_{w}\) and \(b_{w,s}\) are the values of the proposed f-MC-SC model, while \(w=1,\dots,6\). The initial values of \(\alpha_{w}\) are the same with those of \(l_{w}\), i.e. ; \((\alpha_{1},\alpha_{2},\alpha_{3},\alpha_{4},\alpha_{5},\alpha_{6})=(6,5,4,3,2,1)\). Again, 31 steps are taken into consideration where \(\alpha_{m}\) increases by \(0.2l_{w}\) in each step. Thus, in the last step, the offered traffic-load values are \((\alpha_{1},\alpha_{2},\alpha_{3},\alpha_{4},\alpha_{5},\alpha_{6})=(42,35,28, 21,14,7)\)Furthermore, note that in Figures 3-9 (a) we do not present the index \"TC\" in the graphical representation of the TC probabilities so as to increase the readability of these figures and (b) the analytical results are represented with different types of lines, while the simulation results are represented with different types of dots. In Figure 3, we present the analytical and simulation TC probabilities results due to the unavailability of CRUs (\(B_{\text{c},\upsilon,\theta}^{\text{TC}}\)) of the f-MC-SC model and the corresponding (analytical) TC probabilities results (\(B_{\text{c}}^{\text{TC}}\)) of the f-SC-SC model.