**4. Conclusions**

We proposed a novel algorithm to manage distributed drone ports with a centralized controller to ensure maximum co-operation between drones and fair allocation of tasks. The main goal of this system is to efficiently assign grounded drones at drone ports with their respective tasks. Our combination of approximation algorithms ensures that the cluster of tasks belonging to each drone port are within the drone's coverage. Second, the drone can perform the maximum number before returning to the drone port to recharge. We show that utilizing the Ant algorithm for our cluster round trip for drones minimizes the distance traveled for each drone. By utilizing this approach, further tasks assigned to an area can be immediately be assigned without the need to recalculate the entire environment.

**Author Contributions:** Conceptualization, J.L.; Methodology, J.K., K.T., T.Z.O.; Software, J.L.; Validation, J.L., Y.Y. and Z.Z.; Formal Analysis, J.L., K.T., T.Z.O.; Investigation, J.K., K.T.; Resources, X.X.; Data Curation, J.K.; Writing—Original Draft Preparation, J.K., K.T.; Writing—Review and Editing, J.L.; Visualization, J.K.; Supervision, C.S.H.

**Funding:** This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2018-2015-0-00742) supervised by the IITP(Institute for Information and communications Technology Promotion).

**Conflicts of Interest:** The authors declare no conflict of interest.
