## 3 Architecture Design
### Traffic Load Prediction  
The satellite communication network connects the space and terrestrial networks by organizing satellites as network nodes. The advancements in on-satellite processing techniques and inter-satellite communication technologies have greatly increased the ability of satellites to analyze information autonomously and communicate directly with each other. To enable information sharing across coverage areas, satellite network routing strategies are responsible for transmitting and distributing inter-satellite data and providing the required Quality of Service (QoS) for various services. As a result, research into satellite network routing strategies is crucial for further advancements in the field.  
Routing algorithms for satellite networks have two main aspects: computing paths with low communication and computation overhead, and adjusting routing choices in real time with network topology changes. A good routing strategy is essential for transmitting large volumes of data across satellite networks. Globally, the demand for IoT traffic from satellite networks is imbalanced, with more traffic in industrialized regions than in less developed areas, mountains, or seas [20]. However, using the conventional shortest path routing algorithm may lead to traffic build-up in some regions due to variable inter-satellite link (ISL) lengths and asymmetric constellation topologies, such as the lowest horizontal ring [18]. Load-balancing routing techniques have been proposed to address this issue. These techniques typically employ either a local strategy, where satellites independently  
Figure 1: Multilayered satellite network.  
choose their routes based on local traffic data, or a global strategy, which uses data on the condition of all traffic globally to make routing decisions from a global perspective. While neither strategy provides the best performance, they offer different advantages and disadvantages [21].  
Three main methods of performing load balancing based on routing already exist according to existing technology: source-based, centralized, and distributed load balancing systems [22]. The distributed load balancing approach operates on the idea that each satellite independently chooses the best way to transmit data, allowing them to react quickly to fluctuations in traffic.  
Load-balancing routing techniques have another fundamental flaw in that they proactively distribute traffic to avoid congestion while only passively doing load balancing to alleviate detected congestion. The fact that these systems are created under the assumption that traffic demand is unknown and random may be an underlying reason for this behavior.  
The majority of satellite routing algorithms currently available are based on those designed for terrestrial networks. Typically, they rely on either the shortest path or the concept of minimum cost.  
Therefore, it is necessary to study and develop dynamic routing to solve the difficulties encountered in the development of satellite networks. The variation in satellite density across latitudes and differences in user distribution result in significant load imbalances within satellite constellations. Further complicating matters, high-load coverage areas shift rapidly due to the high speed of satellite movement. As a result, traditional routing algorithms have become increasingly insufficient for the demands of modern satellite networks.  
Demands for information transmission and collection have outstripped the capabilities of ground-based communication networks. As a result, research on satellite networks has gained popularity. This is due to their ability to overcome geographical limitations and provide an inexpensive, stable, and reliable means of communication.  
The resolution of inter-satellite routing problems is a prerequisite for utilizing satellite networks. The performance of routing has a direct impact on all aspects of satellite network operation, making it imperative to find an effective solution.