### A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in HWN Using BD Analytics
In the work, for flexible resource management, it is proposed to estimate the system throughput, because as the number of users increases \(H_{input.ij}\), the available throughput \(C_{\text{free}}\) decreases, which in turn leads to an increase in the service delay time and the growth of lost data, as shown in Figure 11.  
For the optimal resource management, a comprehensive calculation method is proposed in this paper, which allows an even distribution of input load in a heterogeneous network. To determine the maximum throughput capacity of a heterogeneous network, we use the following formula:  
\[C_{max}=\sum_{n=1}^{5}C_{max.ij}, \tag{19}\]  
where \(C_{max}\) is the maximum heterogeneous network throughput and \(C_{max.ij}\) is the maximum throughput of \(i\)-\(th\) technology of \(j\)-\(th\) service, \(n\) is the number of technologies in the heterogeneous network. \[C_{max.ij}=P_{max.ij}\cdot C_{QoS,j}, \tag{20}\]  
where \(C_{QoS,j}\) is the throughput needed to provide \(j\)-\(th\) service. Maximum allowable number of active user sessions for different technologies (\(P_{max.ij}\)) is presented in the Table 1 and services throughput requirements (\(C_{QoS,j}\)) are shown in Table 2.  
After calculating the maximum throughput of the network, proceed to the calculation of the throughput allocated to serve the current active sessions. \[C_{cur.ij}=P_{cur.ij}\cdot C_{QoS,j}, \tag{21}\] \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Technology/Service** & **2G** & **3G** & **4G** & **Wi-Fi** & **Cloud-RAN** \\ \hline Call & 1000 & 500 & 500 & 200 & 500 \\ Conference & 0 & 100 & 200 & 150 & 400 \\ IPTV & 0 & 50 & 100 & 150 & 200 \\ Web & 0 & 50 & 100 & 100 & 200 \\ Internet (download) & 0 & 50 & 100 & 150 & 200 \\ Internet (upload) & 0 & 100 & 200 & 250 & 400 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Maximum allowable number of active user sessions for different technologies (\(P_{max.ij}\)). Figure 11: Influence of the parameter of the current system throughput utilization on latency and losses of data. where \(C_{cur.ij}\) is the throughput of the \(i\)-\(th\) technology of the \(j\)-\(th\) service, allocated for active sessions. \[C_{cur}=\sum_{n=1}^{5}C_{cur.ij}=C_{cur.2G}+C_{cur.3G}+C_{cur.4G}+C_{cur.w}+C_{cur.c}, \tag{22}\]  
where \(C_{cur}\) is the total throughput, allocated by the heterogeneous network to serve the current load. For each of the technologies it is necessary to calculate the current throughput. Consider an example of calculating throughput for each of the technologies:  
\[C_{cur.2G}=P_{cur.call}\text{-}C_{QoS.call}, \tag{23}\]  
\[C_{cur.3G}=P_{cur.3 Gcall}\text{-}C_{QoS.call}+P_{cur.3 Gcnt}\text{-}C_{QoS.3 Gconf }+(P_{cur.3 Gid}+P_{cur.3 Gup})\text{-}C_{QoS.i}+P_{cur.3 Gweb}\text{-}C_{QoS.web}+P _{cur.3 Giptv}\text{-}C_{QoS.iptv}, \tag{24}\]  
\[C_{cur.4G}=P_{cur.4 Gcall}\text{-}C_{QoS.call}+P_{cur.4 Gconf}\text{-}C_{QoS.4 Gconf }+(P_{cur.4 Gid}+P_{cur.4 Gup})\text{-}C_{QoS.i}+P_{cur.4 Gweb}\text{-}C_{QoS.web}+P _{cur.4 Giptv}\text{-}C_{QoS.iptv}, \tag{25}\]  
\[C_{cur.c}=P_{cur.call}\text{-}C_{QoS.call}+P_{cur.cconf}\text{-}C_{QoS.4 Gconf }+(P_{cur.id}+P_{cur.idp})\text{-}C_{QoS.i}+P_{cur.web}\text{-}C_{QoS.web}+P _{cur.ciptv}\text{-}C_{QoS.iptv}, \tag{26}\]  
\[C_{cur.w}=P_{cur.wall}\text{-}C_{QoS.call}+P_{cur.won}\text{-}C_{QoS.4 Gconf }+(P_{cur.wid}+P_{cur.wistp})\text{-}C_{QoS.i}+P_{cur.wweb}\text{-}C_{QoS.web}+P _{cur.wistptv}\text{-}C_{QoS.iptv}, \tag{27}\]  
We proceed to calculate the throughput to be allocated for requests coming from users. \[C_{req}=\sum_{j=1}^{6}P_{req,j}\text{-}C_{QoS,j}, \tag{28}\]  
where \(C_{req}\) is the throughput needed to serve incoming requests from users in a heterogeneous network. \[C_{loss}=C_{max}-(C_{req}+C_{cur}). \tag{29}\]  
where \(C_{loss}\) is the throughput which is lost if the number of requests exceeds the maximum permissible values for theinfluence of the parameter of the current system throughput utilization on latency and losses of data.