Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach

Aydin, Esin Ece; Akcasoy, Alican; Cakir, Furkan; Cansiz, Berna Simsek; Secinti, Gokhan; Canberk, Berk

Abstract

Self-organization is a key strategy for improving the performance of an aerial swarm ad hoc network. The proliferation of low-cost VTOL drones has broadened the application domain of aerial swarms, and the need for synchronized communication among network entities has become crucial. However, existing ad hoc approaches struggle to maintain multi-hop connections in contested environments characterized by frequent topology changes and intermittent links. To overcome these limitations, we introduced STDMA protocol, which enables the self-configuration of drones without reliance on a ground controller. In continuation of the earlier work, we conduct extensive experiments to evaluate the performance of the proposed protocol. Comparative simulation experiments cover various scenarios with different network sizes, frame lengths, and traffic loads. The STDMA protocol achieves optimal access delay in highly contested environments and reduces delay by approximately 19.181%. Moreover, it exhibits improved channel utilization compared to the E-ASAP/SM protocol, with a 4.5 times increase.

Citation

Aydin, E. E., Akcasoy, A., Cakir, F., Cansiz, B. S., Secinti, G., & Canberk, B. (2024). Distributed TDMA Scheduling for Autonomous Aerial Swarms: A Self-Organizing Approach. IEEE Access, 12, 45631-45643. https://doi.org/10.1109/access.2024.3381859

• Journal Article Type: Article
• Acceptance Date: Mar 17, 2024
• Online Publication Date: Mar 25, 2024
• Publication Date: 2024
• Deposit Date: Apr 18, 2024
• Publicly Available Date: Apr 18, 2024
• Journal: IEEE Access
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Pages: 45631-45643
• DOI: https://doi.org/10.1109/access.2024.3381859
• Keywords: Ad hoc networks, autonomous control, decentralized control, distributed systems , reliable communication, self-organizing network management, swarm intelligence, UAV swarm
• Public URL: http://researchrepository.napier.ac.uk/Output/3595870