# Hierarchical Resource Management for Mega-LEO Satellite Constellation
## 8 Conclusions and Future Works
### Future Works  
The mega-LEO satellite constellation represents a vast space communication system characterized by numerous nodes, a complex configuration, and a dynamic topology. Operating within a limited resource environment and an open electromagnetic setting, this system may lead to unpredictable outcomes. Consequently, resource scheduling becomes significantly more complex. In the future, several key considerations will need to be addressed to manage these challenges effectively:  
* The global spectrum database. To create a comprehensive database of spectrum resource data, researchers must collect and collate information from various regions and satellite systems worldwide. This involves understanding international regulations set by the ITU, national and regional policies enforced by spectrum authorities, and the actual spectrum currently in use. The database should incorporate real-time updating and querying functions to facilitate efficient management and planning of spectrum resources.
* Endogenous intelligence in resource management. Adding artificial intelligence (AI) models or machine learning frameworks to big data processing platforms is a promising approach for analyzing resource scheduling data and recognizing patterns. To utilize these advanced tools effectively, researchers must first become familiar with the basic operations of AI frameworks. They also need to learn how to apply these tools to large datasets, ensuring they can extract valuable insights and make informed decisions.
* Fusion of AI and computing. To build an intelligent communication ecosystem in the industry, a distributed intelligent platform in the form of software is required. This platform provides intelligent services by supporting the hardware computing resources necessary for intelligent applications to run. Additionally, it offers connection services and integrates intelligence, computing, and connection through network resources. However, this increases the complexity of managing and scheduling integrated services. To achieve optimal scheduling and arrangement, comprehensive service discovery, process arrangement, resource scheduling, and performance measurement are necessary.
* Novel beam-hopping strategy. Beam-hopping resource allocation with a full frequency band is a novel direction that considers priority, service data scheduling, and network load balance. In this study, these factors are treated as critical inputs for resource allocation algorithms. To account for these inputs, algorithms may need to be modified in several ways. For example, different priorities can be assigned to various types of services or users to ensure that high-priority services have sufficient bandwidth and time slots when resources are limited. Ensuring efficient service data scheduling and maintaining load balance across the network are also important considerations.  
Conceptualization, L.G. and D.B.; methodology, L.G.; software, Y.N.; validation, Y.N. and Y.S.; formal analysis, L.G. and G.Z.; investigation, L.G. and H.Z.; resources, L.Z.; data curation, L.G.; writing--original draft preparation, L.G.; writing--review and editing, L.G. and Y.N.; visualization, L.G. and Y.N.; supervision, D.B.; project administration, D.B.; funding acquisition, G.Z. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (NSFC) under Grant U21A20450.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.  
Abbreviations  
3C  
Caching, computing, and communication  
AR  
Available resources  
ASA  
Actual service area  
BER  
Bit error ratio  
BF  
Beamforming  
BFS  
Breadth-first search  
BSs  
Base stations  
CCI  
Co-channel interference  
CR  
Cognitive radio  
CoLoS  
Common line-of-sight  
DA  
On-demand access  
DBF  
Digital beamforming  
DRL  
Deep reinforcement learning