# Predictive Energy-Aware Routing Solution for Industrial IoT Evaluated on a WSN Hardware Platform
## 5 PEAR Solution: Hardware Integration and Results Evaluation
### The Multiple Profiles Test Series
However, regardless of the configuration, the PEAR algorithm determines an average of 2.31 times larger cluster lifetime compared with the Non-PEAR variant. This observation also emphasizes that PEAR can provide energy balancing (1) within large clusters of 65 devices, (2) between clusters with 24 months configured lifetime difference, and (3) for different field device distributions per cluster. The energy profile is respected for the PEAR test configurations where the low-profile field devices represent up to 71.5% of the total number of devices. A larger low-cluster size creates simultaneously two energy balancing constraints namely, (1) a greater need for intercluster energy balancing and (2) a smaller number of devices from the higher profile that can act as sink nodes. Moreover, as indicated in \"Scenario 1\", an energy profile of 150 DPDUs/min does not give an energy margin large enough for a 70 devices cluster to have a 32 months lifetime. Consequently, PEAR enables a small number of high-profile nodes to enhance the lifetime of large low-profile cluster. Table 5 gives the cluster overconsumption for all test configurations. The PEAR energy balancing support eliminates or lowers the cluster overconsumption by at least one order of magnitude thus, confirming the PEAR ability to discover and exploit the energy balancing potential within a network. Figure 12: Comparison between PEAR-Enabled and PEAR-Disabled low cluster lifetime for different cluster configurations. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Test Configuration**} & \multicolumn{2}{c}{**Low Cluster Overconsumption**} & \multicolumn{2}{c}{**High Cluster Overconsumption**} \\  & \multicolumn{2}{c}{**[mWh/day]**} & \multicolumn{2}{c}{**[mWh/day]**} \\  & **PEAR** & **Non-PEAR** & **PEAR** & **Non-PEAR** \\ \hline H50L20 & 0 & 80.19 & 0 & 45.20 \\ H40L30 & 0 & 14.35 & 0 & 147.34 \\ H30L40 & 0 & 569.93 & 0 & 20.19 \\ H20L50 & 0 & 915.88 & 0 & 173.37 \\ H15L55 & 11.29 & 968.97 & 0 & 14.30 \\ H10L60 & 54.28 & 648.30 & 0 & 0 \\ H05L65 & 29.01 & 1334.50 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The PEAR and Non-PEAR cluster overconsumption per test configuration. A configuration having a smaller number of high-profile devices has a lower average energy margin per network and a lower intercluster balancing potential. Therefore, the need for using the energy potential in the network is greater when distributing fewer devices in the high cluster. The results in the Table 5 confirm this by emphasizing that the Non-PEAR low cluster overconsumption is 80.19 mWh/day for a H50L20 configuration and 1334.50 mWh/day for a H05L65 configuration. Moreover, PEAR discovers and exploits more the energy balancing potential as the need is higher and the average energy margin decreases. For instance, PEAR lowers the overconsumption with only 14.35 mWh/day for the H40L30 configuration. However, for the H05L65 configuration when the average energy margin is the lowest it reduces the cluster overconsumption almost with 1305.49 mWh/day, which is 90 times more compared with H40L30 configuration. The second scenario comprises 70 field devices distributed in three profile clusters. The clusters are differentiated by the number of field devices and the energy profiles of 12, 24 and 48 months, respectively. The reference battery capacity is considered 20 Ah or, equivalently 72 Wh. The scenario parameters are summarized in Table 6.  
The low cluster devices are the last ones to join the network thus, being placed on higher topology layers and having less routing load. Due to the favorable deployment setup, no further topology changes are required for the low-profile devices to respect their intended lifetime. However, the deployment setup alone, while advantageous, does not assure compliance with the energy requirements for higher power consuming clusters. The PEAR algorithm improves the mid- and high cluster lifetime with 79% and 23%.