# Compression-Aware Aggregation and Energy-Aware Routing in IoT-Fog-Enabled Forest Environment
## 6 Conclusions and Future Works  
Forest management is very much needed to improve environmental sustainability and maintain the biological balance in the world. Much real-time research is going on for better communication in the forest region with the evolution of IoT. Smart forest management is done with the deployment of sensor nodes and communication among them, which will take more energy. Since the nodes are battery powered, there are possibilities for energy constraints in remote monitoring. To extend the lifetime of the network, aggregation and data compression along with routing are proposed in CAA-ERPL. The proposed CAA-ERPL has three phases. First, based on the transmission range, aggregator nodes are chosen for each forest region. Next, each region node communicates with its aggregator. Finally, routing based on RPL is framed by using ETX and energy as objective functions for all aggregators. The performance of the proposed CAA-ERPL protocol is compared with E-RPL in Contiki Cooja based on metrics such as overhead, end-to-end delay, CPU power utilization, number of parent changes in DODAG, and PDR. From the analysis, it has been observed that the proposed CAA-ERPL is better than E-RPL.  
In the future, the work can be extended to implement various real-time sensors related to forest monitoring and communicating the data packets using aggregator nodes via energy-based RPL to validate the performance. To improve the performance of the sensor nodes and the lifetime of the network, optimization can be done in the Fog node or border router placement that will help to communicate and process the intermediate real-time data. Lastly, the fuzzy-based approach can be integrated by choosing the best residual power and ETX objective function in CAA-ERPL towards forming the DODAG for effective performance.  
Figure 10: CPU utilization vs. scalability of the network.  
**Author Contributions:** S.S. ([PERSON]): conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing--original draft, writing--review and editing, visualization. S.S. ([PERSON]): conceptualization, methodology, formal analysis, investigation, writing--review and editing, visualization, project administration. J.J.P.C.R.: writing--review and editing, methodology, investigation, supervision, visualization, funding acquisition. S.K.: writing--review and editing, visualization, funding acquisition. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work is partially funded by FCT/MCTES through national funds and, when applicable, co-funded EU funds under the Project UIDB/50008/2020; by the Ministry of Science and Higher Education of the Russian Federation, Grant 08-08; and by the Brazilian National Council for Scientific and Technological Development--CNPq, via Grant No. 313036/2020-9.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.