## 5 Experimental Results
### Experimental Results for BCC Algorithm
#### 5.2.2 Power Consumption Analysis of BCC  
Here we discuss the model and parameters used in power estimation followed by the results. Power Model for BCC:  
It was not a straightforward task to estimate the actual electrical power consumed by an HPC data center. The power consumption depended on several internal factors such as utilization of computing power, the cooling mechanism, and data center networks. Data center power consumption was also affected by external parameters like the geographical location, weather, temperature, and humidity. The total IT power consumption of a data center, \(P_{IT}\) consisted of power consumption of the servers (\(P_{Server}\)) and network component (\(P_{Network}\)) of the HPC data center. Hence,  
\[P_{IT}=P_{Servers}+P_{Network} \tag{21}\]  
A major portion of \(P_{IT}\) comes from \(P_{Servers}\)[50; 51]. However, the power consumption of servers varies significantly with the change in CPU utilization [45]. If the utilization of \(i\)-th server is denoted by \(u_{i}\), the Power consumption of that server can be given by \(P_{Server}(u_{i})\), where the dependence of server power on utilization is adopted from [52]. Hence, Equation (21) can be rewritten as:  
\[P_{IT}=\sum_{i=1}^{N}P_{Server}(u_{i})+P_{network} \tag{22}\]  
For the power analysis, we used the power profile of Dell Inc. PowerEdge C5220 (Intel Xeon E3-1265 LV2) servers. Power consumption at different server utilization was modeled from the measurement done by the Standard Performance Evaluation Corporation's \(SPECpower\_ssj\)2008 database for the same server [52]. In addition to the above power model for the server, we considered an idle server to be placed in the PowerNap state [45] with minimal power consumption. The power profile of a server against different utilization is shown in Figure 7. Although compared to the server power, the power consumption of the network of an HPC data center was small, but it was not negligible [50]. One of the issues with the networking equipment was that they needed to be turned on all the time. The static power portion of the networking equipment dominated the total power consumed by the network [53]. In [53], it was shown that for a network switch, only 8% power reduced during full load to no load transition. Moreover, for the wired network, upper-level switches experienced a similar amount of traffic before and after the consolidation as the majority of the flows remained inside of the rack. For this reason, we neglected the change in networking power equipment due to the variation in injection rate or throughput. We estimated power consumption for wired DCNs using commercially available data from Cisco network switches [54] and Silicon network interface cards (NIC) [55]. The power consumption of each device used in the network is shown in the Table 2. The total network power is:  
\[P_{Network}=N_{Core}P_{Core}+N_{Agg}P_{Agg}+N_{Acc}P_{Acc}+NP_{NIC}, \tag{23}\]  
where \(N_{Core}\), \(N_{Agg}\), \(N_{Acc}\), \(N\) are the number of cores, aggregation, access switches, and the total number of servers, respectively; \(P_{Core}\), \(P_{Agg}\), \(P_{Acc}\), \(P_{NIC}\) are the power consumption of an individual core, aggregation, access switches, and network interface cards, respectively. In S2S-WiDCN, however, no core, aggregate or access layer switches were needed, but only antennas, transceivers and NICs were required for wireless communication. The power consumption of the wireless 60 GHz transceiver was modeled based upon the assessment of 60 GHz transceivers [56]. The NICs of S2S-WiDCN were equipped with transceivers for horizontal and vertical communication. In the traditional DCN, external connections were established via the two Cisco 7702 switches. To provide equivalent connectivity in S2S-WiDCN, we employed two servers to work as gateways, and their power consumption wasmodeled as that of the Cisco 7702 switch.