Wind-Aware Service Provisioning Strategy for Multi-Package Drone Delivery

Jia Xu, Hao Liu, Xiao Liu, Azadeh Ghari Neiat, Xuejun Li, Yun Yang

Abstract: In recent years, drone delivery has drawn significant attention for its promising potential in solving the last-mile delivery problem. As a novel service paradigm, Drone-as-a-Service (DaaS) is emerging as an effective way to address service provisioning problems within complex delivery networks. However, existing DaaS composition frameworks often fail to consider the sharing of delivery services and are not applicable to multi-package drone delivery tasks. Meanwhile, as one of the most critical real-world environmental factors for drones, the impact of dynamic wind conditions is not adequately considered by existing studies. This may lead to Quality of Service (QoS) degradation of delivery services. To address the above issues, in this paper, we propose a wind-aware service provisioning strategy for multi-package drone delivery. Given the advantages of Edge Computing (EC) in handling such dynamic factors due to its low latency and high reliability, we first establish a spatio-temporal DaaS model based on service sharing according to the edge-based drone delivery system. Then, we propose a novel wind-aware drone delivery service provisioning strategy for multi-package delivery to minimize energy consumption of drones. The proposed strategy consists of two phases: service sharing and service composition. In the service sharing phase, the service sharing plan is generated by an improved genetic algorithm. In the service composition phase, the edge server dynamically generates the service composition plan through our proposed policy iteration based DaaS composition method. Experimental results using real delivery network and wind data demonstrate that our strategy is able to reduce delivery energy consumption of drone by about 10.1%.

External IDs:doi:10.1109/tsc.2025.3592374