# ARAAC: A Rational Allocation Approach in Cloud Data Center Networks
## 3 Simulation Results
### Discussion
Indeed, if we assume the case in which a group of bidders show a non-cooperative behavior at auction round \(t\), this necessarily means no allocation for such bidders in the next round(s). Having such case repeated for a few rounds with other bidders leads to a state in which the majority of the bidders have a non-cooperative behavior record that certainly puts the model in a deadlock state [6]. ARAAC has a different selection criteria, it deploys a _hybrid selection algorithm_ that looks for those bidders who offer reasonable price-units and who have a positive _accumulative_ reputation record. This allows a room for forgiveness. Such selection criteria are expected to choose those who can provide for both: profits gains and resource utilization. To evaluate these assumptions, Figures 1-3 present the performance outcomes when the aforementioned three mechanisms (ARAAC, Tit-for-Tat, and SBP) were deployed in the conducted simulation environment. Figure 1 shows the resource utilization rates of five different auction rounds, \(t\), labeled on the time axis from 1 to 5. Analyzing the figure, we can conclude that the Tit-for-Tat mechanism scored the highest records, while the SBP scored the lowest. This was predictable; indeed, the Tit-for-Tat mechanism is very selective when it comes to the bidders' behavior in the last won auction round, and it only accepts those bidders with a positive behavioral record. Thus it results in high utilization rates. On the contrary, the SBP does not show any attention to the bidders behavior but for the offered price-units which justifies the low scores it provided. When it comes to ARAAC, the offered price-units and the bidders' behavior are both important, however, the behavior here is accumulative. Therefore, if compared to the other two mechanism, ARAAC shows an intermediate score at the first few rounds, and with the time, it begins to approach the Tit-for-Tat rates as its behavioral policy prevails and the tenants' behavior becomes more mature. In Figure 2, we show the resulting profit values for the cloud-DCN providers at the five auction rounds labeled on the time axis from 1 to 5. Analyzing the figure, we can easily notice that the Tit-for-Tat mechanism earned the lowest profits, while it was clearly higher for the SBP which seeks only the high bid offers. Intuitively, adopting a mechanism that selects the bidders according to their behavioral records regardless of their offered price-units provides no guarantees of profit maximization. In turn, the SBP won the maximum profits in almost all the auction rounds. This is also intuitive, as it seeks for the bids with the highest offered price-units no matter their behavioral records. At the first few rounds, ARAAC earnings were averagely between those of the other two mechanisms. However, at rounds 4 and 5, ARAAC showed close results to those of the SBP. This agrees with our claim that ARAAC provides for an incentive compatible allocation model. Indeed, as the time continued, ARAAC's behavior-based selection policy prevailed, and thus, it motivated those rational bidders who wanted to win the allocation auctions to adapt their behavior accordingly. Figure 3 plots the acceptance rates of the three different allocation mechanisms. The results show that ARAAC has the lowest number of _highly selected_ accepted bids. This sheds light on the selectiveness of the proposed allocation criteria. Obtaining such low acceptance ratio, with increasing resource utilization rates that approach those of the Tit-for-Tat mechanism with high profits, puts the ARAAC first when compared to the other two allocation mechanisms. Never the less, it is worth highlighting that for a cloud-service provider, it is much more preferable to serve/manage fewer cooperative numbers of service tenants as long as they provide for high utilization and profit rates. Figure 1: Bandwidth utilization rates of the simulated allocation mechanisms. Figure 2: Profit gains of the simulated allocation mechanisms.