# Predictive Energy-Aware Routing Solution for Industrial IoT Evaluated on a WSN Hardware Platform
## 6 Conclusions  
One of the main concerns for IWSNs is related to the efficient use of energy and the lifetime predictability of the sensors deployed in the field. IWSN energy efficiency solutions should be tailored to the specifics of the application and should not impact the performance of industrial IoT systems. For instance, the ISA100.11a and WirelessHART industrial communication standards are designed to ensure deterministic data collection, bounded delay, self-healing communication paths and data security. They serve as industrial control and monitoring systems carrying time and integrity critical data.  
This research defines a top-down approach framework for adding energy awareness within IWSNs. In particular, predictive energy-aware routing (PEAR) implements this framework for IWSNs deployed in critical and harsh environments, respecting the ISA100.11a communication standard and embedded on the VR950 Gateway platform.  
PEAR's scope is to provide predictable sensor lifetime and observe the field device energy profile by the means of energy-aware routing.  
The impact and performance of PEAR are evaluated on an ISA100.11a network comprising 70 field devices logically split into one, two or three profile clusters. Moreover, key performance indicators such as cluster lifetime, overconsumption, average consumption, and success rate are compared for PEAR and Non-PEAR variants, respectively.  
The results show that PEAR adjusts the network topology and routing paths to ensure the expected cluster lifetime for network configurations with one or multiple clusters. Furthermore, multiple field device distributions were considered, further emphasizing the PEAR solution relevance for a variety of deployment configurations.  
Concluding, if the energy margin (defined as the difference between the energy profile and the average field device consumption) is at least 50 data packets/minute, the PEAR solution can ensure the expected cluster lifetime. Moreover, PEAR extends the cluster lifetime by up to 3.2 times while reducing the average energy consumption by 23.6% and the total overconsumption 10.4 times after triggering 210 network topology changes.  
In future work, the energy awareness conceptual model could be particularized for other WSN applications by using a top-down approach. Finally, PEAR could be extended to implement additional IWSNs standards such as WirelessHART aiming for a dual-standard PEAR solution.  
Conceptualization, E.J. and C.P.; methodology, E.J. and E.P.; software, E.J. and C.P.; validation, E.J.; formal analysis, O.R. and E.P.; investigation, E.J., C.P., O.R. and E.P.; resources, O.R.; data curation, E.J. and C.P.; writing--original draft preparation, E.J., C.P., O.R. and E.P.; writing--review and editing, E.J. and E.P.; visualization, E.J.; supervision, E.P.; project administration, O.R. and E.P.; funding acquisition, O.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The ISA100.11a certified devices employed in the experimental setup were provided by Control Data Systems SRL, Cluj-Napoca, Romania.  
The authors declare no conflict of interest.