## 4 Body-to-Body Communication and Connectivity
### Real Indoor Experiment Scenario: A Wireless Body-to-Body Connectivity Evaluation  
In order to evaluate the connectivity in indoor wireless body-to-body network scenario, we rely on the recent routing approach (i.e., Optimized Routing Approach for Critical and Emergency Networks: ORACE-Net) which is designed specifically for disaster scenario. The scenario consists of a group of people (we are considering two rescuers in this work) moving in/out an office inside a building following a disaster mobility pattern generated by Bonnmotion [38], which is a mobility scenario generation and analysis tool. Each WBAN consists of an android mobile node collecting live data from on-body Shimmer [39] sensors as depicted in Figure 5b. Additionally, four tactical static nodes (numbered from 2 to 5 in Figure 5a) are deployed during the disaster scenario which represent a temporary backbone through which data is routed to Internet. A dedicated node in the network is considered as a gateway, called a command center node (CC) placed in the back gate of the office as shown in Figure 5a. The CC relays data from the deployed network to Internet and vice versa. Our emphasis of the evaluation mainly concerns the connectivity of the WBAN mobile nodes. To that end, the tactical nodes placements are selected as such to enhance the signal propagation and as a result increase the end-to-end connectivity between mobile WBANs and Internet (through the CC node). Experiment scenario map is depicted in Figure 5a. The experimental parameters are given in Table 3. \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline \multicolumn{2}{c}{_General Settings_} \\ \hline
**Parameter** & **Settings** \\ \hline Number of WBANs & 2 \\ ORACE-Net Tactical Devices & 4 (raspberry pi 2) OS: Raspbian v8.0 \\ Mobile nodes (coordinators) & 2 (Samsung Galaxy S3-I9300-rooted) OS: Android 4.2.2 CyanogenMod 10.0 \\ Wireless mode & Ad hoc \\ ESID & CROW2 \\ Wireless standard & IEEE 802.11n/2.412 GHz (Channel 1) \\ Transmission power & 0 dBm \\ Experiment area & 30 m \(\times\) 150 m \\ CC-node connection & Ethernet to Internet \\ Number of iterations & Ad hoc WiFi to ORACE-Net network \\ Experimentation duration & 60 min/iteration \\ \hline \multicolumn{2}{c}{_ORACE-Net Protocol and Application Layer Settings_} \\ \hline Application layer & MQTT client used for pushing data to the IoT platform \\ MQTT msg size/intervals & 30 Kb/1 s \\ Hello/ADV packet size & 20/25 Bytes \\ Hello/ADV intervals & 3 s \\ Multicast address/port & 224.0.0.0/10000 \\ \hline \multicolumn{2}{c}{_Shimmer_[39]_Sensing Device Settings_} \\ \hline Wireless standard & Bluetooth IEEE 802.15.1 \\  & Pressure, Temperature, Gyroscope \\ Sensed data & (\(x,y,z\), axis-angle), Acceleration (\(x,y,z\)), \\  & Magnetometer (\(x,y,z\)), Battery level \\ Device/Body & 1 (with multiple embedded sensors) \\ Buffer [39] & 1024 bytes \\ Message interval & 1 s \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental parameters and configuration settings. ORACE: Optimized Routing Approach for Critical and Emergency Networks; CC: command center node. Data collected from on-body sensors is routed from WBAN node through the other WBAN node and/or tactical deployed nodes. By reaching the CC node, data is pushed through Internet to the IoT platform. On the IoT platform, data is plotted instantly as depicted by the curves shown in Figure 5b. The WBAN node behavior during the experiment is observed as depicted by Figure 6. The end-to-end link quality estimation (i.e., \(E2E_{LQE}\)) is a real-time metric calculated between a mobile node and the CC node. The bottom curve of Figure 6 illustrates the \(E2E_{LQE}\) results over the time. There is a strong correlation between \(E2E_{LQE}\) and the \(HOP_{Count}\). It is observed that when the mobile node reaches more than 3 hops away from the CC node, and maintains that \(HOP_{Count}\) for more than 2 s, the \(E2E_{LQE}\) decreases sharply. When the \(E2E_{LQE}\) decreases significantly, connection latency increases and leads to mobile node disconnection.