## 5 Challenges and Future Research Directions
### Existing Challenges  
Compared to traditional TNs, SAGINs integrate air-, space-, and ground-based networks and are gradually incorporating maritime communication, which makes the communication environment more dynamic and complex. Currently, UAV-assisted SAGINs face the following challenges:  
1. _Mobility and Dynamic Topology:_ UAVs have high mobility and can access networks at any time and anywhere, causing the network nodes and link states in SAGINs to constantly change. Therefore, more effective routing algorithms and communication protocols are needed to fully cope with the effects of dynamic topologies. For instance, existing SAGIN routing protocols can be extended to dynamically adjust routing rules based on environmental conditions. [PERSON] et al. [158] extended the CAIN, a post-disaster 6G routing protocol, to adapt to SAGIN scenarios by utilizing UAV relays to connect to satellites, thereby further expanding network coverage. [PERSON] et al. [159] proposed a DRL routing strategy based on GANs to enable dynamic routing and ensure network load balancing. Additionally, simulation methods addressing the dynamic topology of SAGINs are noteworthy for advancing research in this field. For example, [PERSON] et al. [160] introduced the SAGINHTE-Stack simulation framework to model the complex dynamics of SAGINs. However, the network's dynamic nature also introduces additional risks for large-scale UAV deployment and trajectory planning. 2. _Intelligent Resource Allocation:_ Dynamic nodes such as UAVs and satellites have limited resources, restricting the communication and computational capabilities of NTNs. Thus, more intelligent resource management and allocation algorithms need to be designed, considering joint optimization issues, especially in dynamic environments. Currently, while NFV and SDN have each achieved significant research progress, their integration with SAGINs remains an area requiring further exploration. By combining AI-driven VNE algorithms and SDN scheduling strategies, SAGINs can achieve efficient resource allocation and scheduling for load balancing under limited-resource conditions. For example, [PERSON] et al. [161] proposed a novel framework to study resource orchestration and allocation for UAV-assisted E2E slicing services in software-defined 6G terrestrial networks. Additionally, AL-based resource allocation methods need further development, and multi-objective approaches specific to SAGINs should incorporate more aspects than those currently discussed. For instance, [PERSON] et al. [162] proposed a joint optimization method for task offloading and UAV trajectory planning. In the future, optimization objectives are expected to encompass even broader directions. 3. _Data and Communication Security:_ UAV-assisted SAGINs create a more open network communication environment, leading to more severe security challenges. Malicious signal interference may result in data loss or communication disruption. Open wireless communication channels are vulnerable to eavesdropping from attackers, and security attacks on NTNs have a huge impact on the security and reliability of networks. This requires close collaboration with advanced data encryption technologies. For cross-layer communication, more general and reliable communication protocols will be essential core issues to address in the future. Moreover, emerging technologies for data encryption, such as blockchain and quantum communication, will offer new solutions for secure communication. For instance, [PERSON] et al. [163] proposed a blockchain-based crowdsensing framework that integrates a reputation incentive mechanism for UAV-assisted mobile crowdsensing, which enhances the security of data sharing. Similarly, [PERSON] et al. [164] proposed a blockchain-assisted data-sharing scheme for Internet of Drones networks, incorporating accountability and privacy protection to improve data privacy and traceability. 4.