# Energy Efficient Routing Protocol in Novel Schemes for Performance Evaluation
## 6 Conclusions  
This examination incorporates an energy-mindful determination of CH, as well as an ideal forwarder hub determination approach, contingent upon a multi-objective way to deal with the determination of CH and altered GSA strategies to track down the best courses. MGSA's utilization of multi-objective models for course disclosure is a key benefit, as the most productive course is found by using the hub's closeness to the CHs, remaining energy, and sensor hub's start-to-finish delay. To expand CH determination, multi-objective factors, for example, the sink distance, remaining energy, and likelihood esteem, are applied. The exploratory outcome shows that the created multi-objective MGSA-ORS strategy saves a ton of energy. The outcomes likewise uncover that, by picking CHs in light of hub distance and utilizing the sink approach, the information conveyance rate and throughput for between group information gatherings moved along. MGSA obtains superior execution with the expansion of multi-objective boundaries. As indicated by the discoveries of the recreations, the proposed MGSA-ORS beat all of the current energy-effective steering conventions in each respect.  
We want to solve for delay-constrained WSN applications by developing another routing scheme that provides the optimal balance of the network's lifespan and delay in multi-hop communication systems. We set up an energy-efficient, clustering-inspired routing protocol in the WSN to improve the node stability and network lifetime; we also designed an artificial bee colony (ABC)-based meta-heuristic scheme, captivated by an efficient cluster-based, energy-efficient routing algorithm in the network to maintain maximum throughput with limited jitter and end-to-end delay.  
Figure 18: Packet delivery ratio.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**TIME** & **FEARM** & **EN—LEACH** & **PROPOSED—ONE FF** & **PROPOSED—TWO FFs** \\ \hline
300 & 0.9400 & 0.9100 & 0.8900 & 0.8600 \\ \hline
600 & 0.9800 & 0.9500 & 0.9200 & 0.8800 \\ \hline
900 & 0.9500 & 0.9300 & 0.9100 & 0.8600 \\ \hline
1200 & 0.9700 & 0.9400 & 0.9100 & 0.8700 \\ \hline
1500 & 0.9700 & 0.9400 & 0.9200 & 0.8600 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Information regarding PDR proposal.  
**Author Contributions:** Authors contributed equally to the development of this work. Conceptualization, formal analysis, data curation, and validation, S.P.; methodology, supervision, Y.K.S.; writing--original draft, validation, C.P. and C.V.; software, writing--review and editing, S.D. and C.V. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** We would like to thank [PERSON] of ECE & Principal of Malla Reddy Engineering College for Women (UGC-Autonomous Institute), Hyderabad-500014, Telangana, India for supporting and enhancing my PhD work for further. We would like to thank you the reviewers for careful verification and approval of our manuscript. The work of [PERSON] supported under UNKP, MIT (Ministry of Innovation and Technology) and the National Research, Development, and Innovation (NRDI) Fund, Hungarian Government. Also, his work supported by Faculty of informatics, Eotvos Lorand University, Budapest, Hungary.  
**Conflicts of Interest:** The authors have declared no conflict of interest.