# UAV Cluster-Assisted Task Offloading for Emergent Disaster Scenarios
## 2 Related Work  
With the advantages of high mobility, low cost, and flexible deployment of UAVs, the applicability of UAVs in various fields is increasing. Therefore, much research has been conducted on the application of UAVs in the field of wireless communication. Because of the flexible communication and unique line-of-sight (LoS) links, most research uses UAVs as airborne wireless relays. On the one hand, UAVs are used to enhance the user service quality in areas with weak communication links, and provide stable and secure wireless communication links for these areas [19; 20; 21]. On the other hand, UAVs are used to expand the network coverage to provide communication coverage within a specified range for areas where no network infrastructure is deployed. [PERSON] et al. [22] proposed a novel UAV-assisted IoT communication network using low-altitude UAVs as aerial anchoring nodes and mobile data collectors, thus assisting ground base stations for device localization and data collection. [PERSON] et al. [23] jointly optimized the UAV flight trajectory and transmission power to minimize the network overhead under the premise of ensuring the quality of service of IoT devices. [PERSON] et al. [24] proposed a deep reinforcement learning-based UAV-assisted communication algorithm to minimize the average channel path loss by optimizing the UAV flight path. In addition, UAVs are used as effective IoT aids, not only as aerial base stations but also for aerial communication, sensing, and data analysis [25]. Recently, UAV-assisted communication networks have been considered for application in post-disaster scenarios where terrestrial wireless infrastructure has been damaged to provide temporary emergency communications for ground users. Because of the advantages of their own hardware, rotary-wing UAVs can be easily deployed in such post-disaster scenarios to provide service coverage for users in specific areas. [PERSON] et al. [26] investigated how to deploy a rotary-wing UAV as a wireless base station in disaster scenarios to provide emergency communication to ground users with unknown distribution, and proposed two UAV trajectory planning schemes based on multi-armed slot machine algorithms to maximize the throughput of the system under UAV resource constraints. [PERSON] et al. [27] proposed a novel hybrid network architecture that uses UAVs to fly along the cell edges to provide computational offloading services to the users around the cell, and effectively improves the minimum throughput for all users by jointly optimizing bandwidth allocation, user partitioning, and UAV trajectories. However, the above work does not take into account the critical energy constraints, especially the limited-resource constraints in the disaster area that will be a crucial factor in extending the lifetime of the UAV-assisted communication network. Optimizing the energy consumption of UAV-assisted communication networks has been of great interest, and several studies have attempted to improve the lifetime and energy consumption of networks by clustering [28; 29; 30; 31]. In [32], the authors describe a comparison of clustering techniques for implementing energy-aware routing in device-to-device (D2D) communication in public safety networks, comparing several different clustering schemes in terms of energy consumption, throughput, and the number of dead nodes in the system through extensive simulation experiments, and the results indicate that the clustering scheme proposed by the authors outperforms the other compared schemes in all aspects. Although extended communication applications for UAVs in disaster scenarios have been extensively researched, there is still a need for continuous exploration to find a UAV-assisted task-offloading solution that can provide reliable services in unknown disaster scenarios.