# Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares
## 4 Conclusions and Future Work  
This paper presents a novel method of communication in quarantined or isolated areas, or areas with technical damage, using networks of drones that fly based on a well-established mission plan and schedule, on 2D surfaces covered by squares. Two situations of drone battery management--charging and battery changing stations--were investigated.  
A network of square cells with two drones in each cell was proposed to cover a geographical area. The drone network was simulated based on input data from experimental flight tests of a quadcopter using six routing algorithms.  
A TD-Drone Dijkstra algorithm (single-copy algorithm) and multiple-copies algorithms were proposed to simulate a Delay Tolerant Network of drones. Results showed a delivery rate ranging from 0.166 to 0.954 in the drone network with battery changing, and from 0.135 to 0.540 in the drone network with battery charging. The best latency of 0.43 h for a drone network with battery changing was obtained using the TD-Drone Dijkstra algorithm. Thus, the best results were obtained for the TD-Drone Dijkstra algorithm, which was able to deliver most of the data packages in the shortest time.  
The traditional DTN algorithms, such as Epidemic, Spray and Wait, and MaxProp, produced lower results due to the small number of contacts between nodes, and a low number of message exchanges. The fastest communication was established for the drone squares network with battery changing. It was found that the battery change scenario led to an increase in the delivery rate of 76% compared to the battery charge scenario.  
It was found that the battery change scenario led to an increase in the delivery rate of ~200% compared to the battery charge scenario.  
The fastest communication was found for the drone triangular network with battery charging, and for the drone square network with battery changing. However, the drone square network is considerably cheaper than the drone triangular network. Thus, if cost is not an issue, the triangle network of drones may be implemented because better performances can be achieved. However, if there is a budget constraint, then the square network type is more suitable.  
In future work, we will aim to apply this network of drones to parcel delivery during emergencies in remote quarantined zones.  
**Author Contributions:** Conceptualization, A.M.D. and R.U.; methodology, R.U. and A.M.D.; software, A.M.D. and C.-S.N.; validation, R.U. and A.M.D.; formal analysis, A.M.D. and R.U.; investigation, R.U. and A.M.D.; resources, R.U., C.-S.N. and A.M.D.; data curation, C.-S.N. and A.M.D.; writing--original draft preparation, R.U., A.M.D. and C.-S.N.; writing--review and editing, R.U. and A.M.D.; visualization, A.M.D. and R.U.; supervision, A.M.D. and R.U.; project administration, R.U. and A.M.D.; funding acquisition, A.M.D., C.-S.N. and R.U. All authors have read and agreed to the published version of the manuscript.  
This research was funded by University Transilvania of Brasov.  
Not applicable.  
The authors acknowledge of Transilvania University of Brasov for providing the infrastructure used in this work.  
The authors declare no conflict of interest.