## 3 Routing in Satellite Networks
### Routing Protocols in LEOs
#### 3.3.5 Dynamic Detection Routing Algorithm (DDRA)  
DDRA is a routing protocol that relies upon an abstract topology snapshot. In the DDRA algorithm, the satellite interval is broken down into n time pieces. The satellite topology in the slices can be presented by one snapshot. Thanks to the DDRA algorithm, low time delay is achieved, and the ability to adjust to shifting network conditions is increased [108]. Standard satellite routing algorithms also encompass Traffic Prediction Distributed Routing Algorithm (TPDRA) [109], Control Route Transmission (CRT) [110], Compact explicit multi-path routing (CEMR) [111], Adaptive Load Balanced Routing (ALBR) [112], Dynamic routing algorithm (DRA) [113], Cross-Entropy Accelerated Ant Routing System (CEAARS) [114], etc. The literature on routing protocols in satellite networks is given in Table 3.  
\begin{table}
\begin{tabular}{c c  
shapes depending on their movements. Depending on the movements of satellite networks in different planes, their distances are also different, which causes the network topology to change. For these reasons, it is not enough to choose the best path from source to destination in satellite networks; it is necessary to maintain this path throughout the communication. The authors worked on more efficient and effective routing models for this purpose. They propose a distributed datagram routing algorithm that creates minimal propagation delay paths, does not cause overhead, and avoids congestion. The proposed system is distributed, with each data packet's path being determined individually. The proposed algorithm has shown successful performance in both congestion avoidance and routing of packets in case of any failure. Should a satellite or ISL malfunction occur, the effectiveness of the recommended algorithm would experience a significant decline [113]. In 2002, [PERSON] et al. focused on creating a proficient resolution for the routing problem within a low Earth orbit (LEO) network. They also addressed the matter of situating the necessary Network Operations and Control Centers (NOCCs) to facilitate the satellite system. In satellite networks, both IP routing and ATM routing are not efficient due to large overheads, inefficient use of bandwidth, and the inability to handle a vast number of routing tables. Since the models arising from the integration of such models have similar problems, a routing model is proposed that is similar to ATM switching and factors in accounting for the memory requirements of the satellites. In the proposed model, the arrangement of the network is portrayed via a collection of snapshots of its topologies. The ground stations pre-calculate the snapshot order and update it using the unpredictable changes detected by the satellites. If the link between satellites and ground stations is severed, the proposed model cannot be executed [115]. In 2010, a routing algorithm for efficient load balancing over satellite networks was studied. Due to the uneven population distribution, some of the satellites of the satellite networks suffer from congestion, and some suffer from underutilization. This problem is becoming more important, especially in LEO satellite networks with low altitudes. Without an effective routing algorithm, the unequal allocation of network traffic can lead to considerable queue delays and massive packet loss in high-traffic areas. This article introduces a decentralized routing approach called agent-based load balancing routing (ALBR), designed specifically for LEO satellite networks. ALBR, which aims to guarantee lower packet loss, better efficiency, and end-to-end latency limits, uses two types of agents: stationary agents and mobile agents. The task of the station agent is to estimate the cost of the ISL (inter-satellite link) on the satellite and update the routing elements. The task of the mobile agent is to discover the routing path and collect routing information. The proposed algorithm has been proven to provide better load-balancing.