Abstract: Low Earth Orbit (LEO) satellites have become important means of communication, and more and more transmission data flow query requests may arrive simultaneously due to the increasing number of users. Existing routing algorithms often prioritize individual data flow efficiency, neglecting satellite occupation and link utilization. This exacerbates queuing time and transmission delay. In this paper, Software Defined Network (SDN) is employed to obtain the information of satellite networks and focus on the overall transmission efficiency of a batch of data flows. A Large-Scale Query satellite routing Algorithm (LSQA) is proposed, which estimates the resources required for each data flow first and intends to find an optimal data flow query execution order to reduce satellite congestion. To speed up the estimation, we construct the node labels, so that the shortest path between satellites can be obtained quickly. Furthermore, we propose a strategy based on threshold filtering to obtain the optimal execution order more efficiently by finding out data flows whose execution order does not affect the overall transmission delay. Extensive experiments conducted on satellite network simulation show that LSQA has the superiority in terms of queuing delay and load-balancing compared with counterparts.
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