# Toward Integrated Satellite Operations and Network Management: A Review and Novel Framework
## 2 State of the Art
### Research Insights and Challenges  
The analysis of existing tools and approaches reveals several critical limitations that motivate the development of the novel integrated management framework. This section presents a summary of the challenges and gaps identified in the literature. The general insights from the literature highlight several key points. First, there is a notable lack of interoperability between network and satellite operators for operations management, prompting various architectural proposals for better integration of satellite and terrestrial networks. Improvement areas include uncertainty modeling, as satellite telecommunications are subject to many uncertainty sources. These can be mitigated through dynamic scheduling, advanced uncertainty modeling, ML, and distributed scheduling. Operations management also plays an essential role in traffic management, with operational data serving as a critical input for optimizing network activities like routing and queuing. In scheduling, centralized approaches face scalability and timeliness issues. In contrast, distributed approaches lack global information or require extensive messaging between satellites, making a hybrid approach advantageous in resource-constrained, uncertain environments. ML emerges as a promising tool for distributed scheduling, enabling efficient adaptation to variable conditions despite onboard resource limitations. The standardization insights reveal that significant efforts are ongoing within 3 GPP to integrate NTNs with terrestrial infrastructure. However, while 3 GPP provides guidelines for satellite-terrestrial integration, it does not cover specific satellite operations, assuming that the necessary adaptations for integration will occur without issue. This gap forms the core focus of our study, which seeks to determine how to operate satellite constellations in compliance with terrestrial network standards, ensuring a seamless integration between the two systems. The insights from sporadic connectivity constellations indicate that commercial satellite constellations, particularly those with sporadic connectivity, typically rely on custom tools and semi-manual procedures for satellite operations, as detailed information on persistent connectivity networks is not publicly available. Research on sporadic constellations focuses heavily on EO missions, with no existing literature that adapts EO satellite task-scheduling methods for telecommunications applications. EO studies emphasize offline task scheduling with task priorities as the main optimization metric, providing valuable but unoptimized solutions for telecommunications needs. While EO algorithms for task scheduling could be beneficial for telecommunications, their performance is often tailored to specific EO scenarios, presenting challenges when applying them to the dynamic requirements of telecommunications. Although EO scheduling algorithms are well-documented, adapting them to telecommunications scenarios remains a largely uncharted area in research. Insights from persistent connectivity constellations and integrated networks reveal that satellite and terrestrial networks are currently developed and operated as separate systems, though much recent work focuses on achieving integration. However, integrating these two network types remains an open challenge, with a consensus in the literature pointing to the need for intelligent, efficient management and orchestration. A multi-layered constellation is often envisioned as the persistent connectivity architecture for integrated satellite-terrestrial networks, where network management is typically based on NFV and SDN as applied in 5G terrestrial networks--a concept now being adapted to NTN. However, most proposed resource management architectures in NTN derive directly from terrestrial network models, often disregarding the specific roles of satellite operators and focusing solely on network metrics.