# Next-Generation Payment System for Device-to-Device Content and Processing Sharing
## 4 Simulation Study and Numerical Results
Figure 1: Sample topology. Axes represent distance in meters. have on their plans and charges on excess data, it is not entirely accurate to say that \(c_{b}=0\) for current practice. One could argue that \(c_{b}\) is effectively \(>0\) under current practice, but within the quota, it could be said that downloading content from the base station is free). In this setting, we see a lot of users with small balances, which illustrates heavy downloading from base station, which makes sense as the cost in this case is 0. As \(c_{b}\) increases, users are discouraged to download from the cloud/base station whenever possible. With growing \(c_{b}\), the proportion of users with balance close to 0 decreases. This is expected, as more users try to download from other users. Moreover, in this scenario, we see many users paying excessive amounts of tokens for content, whereas we do not see as many users that capture the demand and make excessive amounts of gains. In this study, we ignored the scenarios where a user cannot download content from other users and/or the cloud/base station due to a lack of credit, hence permitting negative balances. This illustrates the expenditure of users under the given scenarios. Further studies need to be conducted to determine optimum pricing policies for the providers, which is left out of the scope for this study. We present average tokens paid for each GOP in Figure 3, as well as the ratio of GOPs that required transcoding from the source user. The average cost of a GOP increases threefold when \(c_{b}\) increased from 0 to 1, whereas it increased almost linearly with a lower slope when \(c_{b}>1\). A similar effect can be observed with the ratio of GOPs that required transcoding. When \(c_{b}=0\), a significant portion of GOPs is downloaded from the cloud/base station, which requires no transcoding. On the other hand, as the cost of downloading from the cloud/base station increased, the share of GOPs downloaded from other users increases, hence increasing the ratio of GOPs that required transcoding. For \(c_{b}>1\), this ratio varies between 6 and 8%, as opposed to the 2% for \(c_{b}=0\). This is in accordance with the ratio of the GOPs downloaded from the cloud/base station, which is provided in Figure 4. The portion labeled \"BS only\" is due to the GOPs that are being downloaded for the first time in the entire cell and, thus, does not exist in any of the users; therefore, they are bound to be downloaded from the base station. This ratio does not change with \(c_{b}\), which is to be expected as the arrival process and the distribution of the video files are not affected. This figure demonstrates that (i) even with the base station providing free content, almost 40% of the GOPs are downloaded in D2D mode since the objective is to maximize quality, and (ii) as soon as \(c_{b}\) becomes \(\geq 1\), downloads from the base station are severely limited, and the exact value of \(c_{b}\) has little effect on the ratio. Figure 2: Cumulative Distribution Function of token balance for different values of \(c_{b}\). In Figure 5, we illustrate the ratio of the quality levels of the GOPs that are played out. One conclusion that can be inferred from this figure is that the average GOP quality is not significantly affected by \(c_{b}\). More importantly, allowing D2D modes significantly improves the average GOP quality, as almost 40% of all GOPs are played out in the worst quality level when the D2D mode is disallowed. The improvement in the share of best-quality GOPs might seem limited, but the share of worst-quality GOPs is drastically decreased with D2D. Figure 4: Ratio of the GOPs downloaded from the cloud/base station (blue: GOPs that do not exist in the cache of any of the users and downloaded from the cloud; red: GOPs downloaded from the base station cache), and GOPs downloaded from other users for different values of \(c_{b}\). Figure 3: Tokens paid per GOP for different values of \(c_{b}\). From Figures 3-5, we observe that the behavior of the system does not drastically change when \(c_{b}>1\).