# Joint Location-Dependent Pricing and Request Mapping in ICN-Based Telco CDNs For 5G
## 5 Evaluation
### Experiment Results
#### 5.2.2 Results of PARM  
On the basis of the prices calculated in the previous part, we further evaluate the performance of the PARM design, compared with another two cases, i.e., BASE and PURM. Figure 8 shows the comparison of variation of CDN sites in four traffic patterns of BASE, PURM, PARM, respectively. We observe that the variation of the former two patterns in BASE is obviously higher than in the latter two patterns. The observation here conforms with the distributions of the sites' congestion level observed in Figures 4-7, respectively. In PURM and PARM, the variations of all traffic patterns are nearly the same. This is because Constraint (4b) (which exists in both PURM and PARM) bounds the target congestion level. For details, variations in traffic pattern 1 and 2 under PURM and PARM are much lower than the relative values under BASE. Variations in the latter two traffic patterns are higher than those in BASE. To quantity the impact of three cases on the telco CDN's cost, we compare total bandwidth cost of all CDN sites in Figure 9. First we observe that bandwidth costs under PURM and PARM are nearly the same in all traffic patterns and are not higher than those under BASE. This observation proves the effectiveness of Constraint (4b) in reducing the total bandwidth cost by making sites' target congestion level fluctuate in certain range. Specifically, PURM and PARM obviously reduce bandwidth cost compared with BASE in former two traffic patterns. In comparison, three cases bring nearly the same bandwidth cost in traffic pattern 3 and 4. That is to say, the variation increase brought by PURM and PARM in the latter two traffic patterns (as shown in Figure 8) is acceptable. Figure 10 shows the total payment for bandwidth in three cases. First, we observe that payments under BASE and PURM are the same. This is because the bandwidth prices are the same in these two cases, i.e., \(P_{const}\), and the total bandwidth usage is unchanged after request direction by PURM or PARM (as constrained by Constraint (4d)). In comparison, payment under PARM is different from that under BASE/PURM due to the location-dependent and congestion-aware features in the LDP strategy. We observe that in Traffic Pattern 2 and 3, which are less congested, payment under PARM is lower than that in BASE/PURM with 7.94% and 10.4% as the reduction ratios, respectively. This is because LDP sets the price lower than \(P_{const}\) when the congestion level is relatively low. Thus, the application providers will save more money if they use more. In contrast, in Traffic Pattern 1 and 4, which are more congested, payment under PARM is higher than that in BASE/PURM with 3.25% and 31.7% as the increasing ratios, respectively. This is because LDP sets the price higher than \(P_{const}\) when the congestion level is relatively high. The higher the congestion level, the higher the  
Figure 8: Comparison of variation of CDN sites. when the overall congestion level of all the CDN sites is high, a telco CDN could be paid more under PARM than under BASE/PURM, thus it will have more economic incentives and be positive in terms of expanding its bandwidth capacity. Figure 11 shows the average latency of all applications in the three cases. First, we observe that PURM and PARM both outperform BASE. This is because they both minimize latency in the optimization and BASE conducts request mapping without considering the latency performance. Then, we compare PURM and PARM and find that in Traffic Pattern 1 and 3, PARM outperforms PURM, and in the other two traffic patterns, PURM outperforms PARM. Yet, it is confirmed that the latency constraint of every application is satisfied. Thus, the result is acceptable. Figure 10: Comparison of total bandwidth payment. Figure 9: Comparison of total Bandwidth Cost.