Formation-based Selection of Drone Swarm Services
This addresses energy efficiency for drone swarm delivery services, though it appears incremental as it builds on existing SDaaS concepts with formation-specific optimizations.
The paper tackles the problem of limited flight endurance in drone swarms for delivery missions by proposing a formation-guided framework for selecting Swarm-based Drone-as-a-Service (SDaaS). It shows that considering swarm formations affects energy consumption and demonstrates efficient algorithms for Fixed and Adaptive selection approaches under extrinsic constraints like wind.
Swarm of drones are increasingly being asked to carry out missions that can't be completed by one drone. Particularly, in delivery, issues arise due to the swarm's limited flight endurance. Hence, we propose a novel formation-guided framework for selecting Swarm-based Drone-as-a-Service (SDaaS) for delivery. A detailed study is carried out to highlight the effect of swarm formations on energy consumption. Two SDaaS selection approaches, i.e. Fixed and Adaptive, are designed considering the different formation decisions a swarm can take. The proposed framework considers extrinsic constraints including wind speed and direction. We propose SDaaS selection algorithms for each approach. Experimental results prove the efficiency of the proposed algorithms.