## 5 Simulation Results
### Experimental Results of Phase II
performance in terms of data packets received by sink is achieved by both approaches while SRMM is followed with marginally less energy expenditure since in SRMM movement pattern does not have any sharp turn or sudden stop. Besides, the speeds are also increased gradually. Thus, LQ is not changed drastically when SRMM is followed to model body movement due to posture change. However, the proposed approach exhibits better performance in terms of data packets received by sink than the existing protocol [17] though the amount of energy consumption is comparable. In the subsequent experiment, the proposed strategy is evaluated in terms of heat generation due to network activities. For this experiment, another metric heating ratio has been introduced which is defined as follows  
\[Heating\ ratio_{i}\ =\frac{\sum_{SAR_{i}>SAR_{th}:i\in n}Time_{i}}{\sum Time} \tag{16}\]  
Heating ratio (\(Heating\ ratio_{i}\)) of any node \(i\) in the network of \(n\) nodes is evaluated as the summation of the discrete timespans for which the SAR results due to node \(i\) (\(SAR_{i}\)) measured following Equations (4) and (5) exceeds its regulatory limit (given in Table 3) with respect to the entire simulation period. The outcome is plotted in Figure 11. It is found from the outcome that the nodes in the network exhibit much low heating ratio as they got heated for small duration while following the proposed strategy. However, the nodes which are closer to sink as shown in Figure 7 for instance node 6, node 7, node 4, etc. produce relatively high heating ratio with respect to other nodes in the network as they often work as forwarder for others as well exploiting their connectivity to sink. Even, the proposed approach shows low heating ratio as compared to the state-of-the-art energy-efficient  
Figure 10: Performance evaluation of the proposed routing strategy with respect to time. (**a**) Variation of data packets received by sink with time following Line Mobility Model (LMM). (**b**) Variation of energy consumption with varying time following LMM. (**c**) Variation of data packets received by sink with time following Smooth Random Mobility Model (SRMM). (**d**) Variation of energy consumption with varying time following SRMM. protocol [17]. Hence, the objective to prevent thermal damage of human tissue is achieved with the designed multi-hop transmission strategy. Finally, the behavior of the proposed strategy is observed with growing network size. Reliability of the proposed work is quantified here in terms of Packet Delivery Ratio (PDR) which is defined as the ratio between total number of packets received by sink to the sum of the packets sent by the nodes presented as follows  
\[PDR\ =\ \frac{\sum_{i}data_{received}}{\sum_{i=1}^{n}data_{sent}} \tag{17}\]  
The experiments started with 5 nodes having connected topology at the beginning and gradually more nodes are included to form a bigger network (up to default network size) to estimate the scalability of the proposed approach. The experiments were carried out following LMM [35] and SRMM [36] for three different data sending rates 14 packets/s, 70 packets/s and 125 packets/s having packet size 2000 bits each (i.e., in other words 28 kbps, 140 kbps and 250 kbps). Results are plotted in Figure 12a,b. Since the number of relay nodes increases with growing network size which enhances the chances to find route to destination for the data traffic, the performance of the proposed protocol improves irrespective of the data sending rate in case of both mobility models. Hence, it is evident from the outcome that the proposed strategy can cope up with the increasing network size while ensuring substantial reliability in terms of PDR. Herewith, the entire experimental procedure can be perceived as an integration of two phases namely Phase I and Phase II. In Phase I, transmission strategy for intra-BAN communication has been formulated following MDP and experiments are conducted to analyze the behavior of MDP  
Figure 6:0 Heating ratio of each node in the network.