# Dynamic Routings in Satellite Networks: An Overview
## 5 Potential Technologies and Future Directions
### Future Directions  
Due to the substantial heterogeneity of multi-layer satellite networks, the frequent changes in the constellation topology, and inter-satellite links, flexible control system reconfiguration is more necessary. The new research direction of routing will undoubtedly become a hotspot in future academic work. Its primary contents are as follows:  
**Multi-scale Information Awareness and Computing In Complex Environments:** The satellite networks contain multiple types of network nodes, and the data acquired by the network nodes in different satellite layers are heterogeneous. To facilitate the processing of massive data information, we must consider unifying and integrating data when designing routing algorithms. In order not to waste many satellite network resources in terms of bandwidth, mobile edge computing (MEC) platforms can be used for big data analysis [131]. Big data analytics can be performed at the edge of the network, and the results are sent to the core network. MEC platforms allow edge networks to gain management access to computing and services to reduce mobile users' network latency and bandwidth consumption. Content optimization is indispensable to better support routing requests that differentiate the quality of service. With MEC, content optimization can be performed dynamically based on user-perceived information. At the same time, edge networks can improve performance, enhance the quality of user experience, and provide new services through content optimization. Furthermore, the use of MEC can improve the routing algorithm's ability to sense the network state. When the network state changes, the algorithm quickly converges and makes a better routing decision. The field of autonomous driving, where edge computing and deep learning are closely integrated, has been carefully studied by several researchers in China and abroad [132; 133]. In the subsequent research, deep learning and reinforcement learning can be used to improve satellite network routing decision making. In particular, improving deep learning technology and expanding MEC's use in satellite networks to boost network performance will be important. **Intelligent Satellite:** An intelligent satellite is an operating system with strong fault tolerance running on a standardized hardware platform. Various types of apps can be developed to carry out satellite applications based on this operating system. Smart satellites have the following typical characteristics: (1) Requirements are definable. The satellite can reconfigure its entire system and respond flexibly to different space mission needs, such as communication, navigation, remote sensing, and scientific exploration, providing a variety of functions and tasks; (2) Software can be reconfigured. The satellite has a consistent program execution environment and a rich set of application software that can dynamically configure and execute apps for different tasks; (3) Reconfigurable functionality. Different functions can be quickly reconfigured by accessing different hardware components and loading different software components. Inter-layer contacts are frequently interrupted in multi-layer satellite networks due to the rapid relative motion between satellites in different layers. The network topology is constantly changing, leading to a frequent dynamic reconfiguration of inter-satellite routes. Hence, building a multi-layer satellite network based on artificial intelligence is the way forward, such as intelligent seamless handoff technology and intelligent interference cancellation technology to respond to dynamic routing effectively. To some extent, we can achieve intelligent communication. In addition, artificial intelligence will become an inherent feature of future satellite networks, including intelligent network elements and network architectures, intelligent connected objects, and intelligent information support services. **Intelligent Routing:** Intelligent routing has three advantages [134]: (1) Accuracy.