Energy-Efficient UAV Deployment and Link Routing in UAV-Assisted MEC Network for Disaster Response

This paper introduces an innovative UAV deployment and link routing mechanism for UAV-assisted Mobile Edge Computing (MEC) networks, designed to rapidly rebuild a temporary communication network in disaster scenarios. Our primary objective is to effectively reduce the total energy consumption of the network while considering UAV battery capacity limitations, thereby significantly extending the network's lifespan. Specifically, this study first formulates a Mixed Integer Linear Programming (MILP) problem, named EEUDR (Energy Efficient UAV Deployment and Routing). To solve this complex optimization problem, we developed an efficient heuristic algorithm called HMEA (Heuristic Minimum Energy Algorithm). Extensive experimental results demonstrate the effectiveness of our approach. Compared to the theoretical optimal algorithm (OPT), HMEA increases total energy consumption by only 14.3 % on average, while significantly reducing algorithm execution time. Compared to two other benchmark algorithms, HMEA demonstrates superior performance by reducing energy consumption by more than 30%. These advantages make HMEA particularly well-suited for the rapid reconstruction of communication networks in large-scale post-disaster scenarios.