Joint Resource Allocation and Task Scheduling for LAWN-Enabled Emergency Response
Abstract
The low-altitude wireless network (LAWN), mainly composed of uncrewed aerial vehicles (UAVs), is a promising paradigm for emergency response. However, the implementation of LAWN requires achieving efficient and reliable coordination among multifunctional UAVs. Therefore, how to guarantee communication reliability and realize coordination among heterogeneous UAVs in unpredictable environments remains a key issue. In this article, we propose a novel LAWN framework, where reconnaissance UAVs first collect situational information, relay UAVs forward the sensed data to the fire station for decision-making, and firefighting UAVs execute material delivery according to the returned commands, thereby forming a closed-loop emergency response. Then, we formulate the optimization problem to minimize the total response delay while ensuring the fairness of multipath routing. To tackle the NP-hard problem, we decompose it into two subproblems of the route construction problem (RCP) and firefighting scheduling problem (FSP). We design the regular geometric topology for the UAV deployment, derive the transmission power in closed form to establish feasible links, and RCP is reformulated into a tractable integer linear programming problem. Then, the gray wolf optimization-based firefighting scheduling algorithm (GWO-FSA) is proposed for the task assignment, resource allocation, and path planning of UAVs. Extensive simulation results demonstrate the effectiveness of the proposed scheme in enhancing the emergency response efficiency.