# GANA-VDC: Application-Aware with Bandwidth Guarantee in Cloud Datacenters
## 4 GANA-VDC System Architecture
### Mapping Procedure
A series of VDCs generated at random was added into the created networks, where only when the sum of rejected VDC allocations goes beyond the threshold of at least 20 times was the algorithm stopped. The results we report represent mean values for 100 measures. Overall, 70,855 allocations (99.86%) were successful out of 70,957 allocations. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Application**} & \multirow{2}{*}{**Percentage**} & \multicolumn{2}{c}{**Core Infrastructure**} & \multicolumn{2}{c}{**Aggregation Layer**} & \multicolumn{2}{c}{**Edges**} & \multicolumn{1}{c}{**VM**} \\ \cline{3-10}  & & **(\%)** & **Size** & **Bandwidth** & **Size** & **Bandwidth** & **Size** & **Bandwidth** & **Size** \\ \hline
**Web** & 50\% & 1 & 1000 & 1 & (1000,2000) & 3 & 500 & (2,6) \\ \hline Enterprise Network & 5\% & - & - & (2,6) & 400 & (2,6) & 100 & (2,6) \\ \hline Storm & 5\% & - & - & 1 & 1000 & 2 & (500,1500) & 2 \\ \hline MapReduce & 30\% & - & - & (2,5) & (500,800) & (2,5) & (500,800) & (2,5) \\ \hline File Backup Service & 10\% & - & - & 1 & (200,1200) & 2 & 200 & (2,6) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Application in Cloud Datacenter Percentage. Figure 9: Application types in cloud datacenter. **Even Allocation:** In Figure 10, the plots of (_pod_util_) have similar trends during all of the VDC allocations in any percentage of the number of VDC allocations, and the (_pod_util_) of most of the pods remain close. Thus, the network resource was evenly allocated among pods. Through three-phase balanced mapping, our algorithm ensured the fair distribution of network utilization during VDC allocation. **High Network Utilization:** We collect statistics of network utilization in Figure 10a. The horizontal axis represents the percentage of the number of the allocated VDCs. The vertical axis indicates network utilization. Figure 10b shows the resources were primarily utilized with our proposed algorithm for VDC allocation: 94% for (_server_util_), and 87% for (_pod_util_) of all the pods on average, and 61% for (_network_util_). When confronted with the first VDC allocation failure, (_server_util_) was close to 82%. Because most of the VN of VDCs comprise two layers, they are supposed to be mapped to the corresponding aggregation layer and edge layer and in the underlying physical network the ratio between the connections between the three layers equals 1:1:1; thus, the bisection bandwidth between the aggregation and the core layers was not used entirely when no bandwidth remains available to the servers. In our experiment, only the enterprise network in the application types occupied three layers. However, its proportion remained low, thus an upper limit of network utilization was set at 65.66% in principle. **Efficient and Scalable Allocation:** To facilitate analyzing the VDC allocation efficiency, the intervals are defined based on the ratios of the volumes of VDC allocations when cloud data center approached heavy loads in Figure 11. Here, we set the interval at 20%. All VDC allocations are points in this figure to depict the allocation times together. Two clear black lines stand out where the lower one refers to the VDC applications with two-layer networks, and the upper one agrees with the data from three-layer networks. A linear fit processing in Figure 11a shows the scalability of the algorithm to perform allocation through these points, as the allocation time scaled almost linearly with the increasing number of VDC. In Figure 11b, the allocation time almost keeps stable with the increasing VNC number, and the moving average stays close to the lower line since most of applications are of two-layer network types. Because most of the applications engender a two-layer network type, the linear fit line usually agreed with the lower black line. This agreement worsened slightly when the number of VDC allocations increased.