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Enabling Self-Organizing TDMA Scheduling for Aerial Swarms

Aydın, Esin Ece; Kara, Omer; Cakir, Furkan; Cansiz, Berna Simsek; Seçinti, Gökhan; Canberk, Berk


Esin Ece Aydın

Omer Kara

Furkan Cakir

Berna Simsek Cansiz

Gökhan Seçinti


With the proliferation of affordable VTOL drones, application domain of aerial swarms expands everyday, spanning from public drone art to offensive military operations. Orchestrating these systems towards a successful mission, especially in contested environments, requires strict synchronization and reliable communication among network entities. Although using a ground controller with a long range link provides a cost-effective solution, it is extremely vulnerable to single-point of failure and/or jamming attacks. Thus, in contested environments, adapting ad-hoc policies is one of the most promising approaches, mitigating these vulnerabilities. However, existing ad-hoc approaches fail to sustain multi-hop connections, suffering from frequent topology changes and intermittent links due to dynamic environment. In this paper, we propose self-organizing TDMA (STDMA) protocol for aerial swarms in order to ensure reliable communication through efficient network management. We also partially implement our protocol on a small-scale test-bed and show that how drones are able to self-configure upon joining the network without any prior information. Our proposed STDMA protocol improves the overall channel utilization up to 55 percent with less control traffic overhead compared to the existing studies.


Aydın, E. E., Kara, O., Cakir, F., Cansiz, B. S., Seçinti, G., & Canberk, B. (2022, June). Enabling Self-Organizing TDMA Scheduling for Aerial Swarms. Presented at MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, OR, USA

Presentation Conference Type Conference Paper (Published)
Conference Name MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services
Start Date Jun 27, 2022
End Date Jul 1, 2022
Online Publication Date Jun 27, 2022
Publication Date 2022-07
Deposit Date Nov 1, 2022
Publisher Association for Computing Machinery (ACM)
Book Title DroNet '22: Proceedings of the Eighth Workshop on Micro Aerial Vehicle Networks, Systems, and Applications
ISBN 9781450394055
Public URL