Content area
Low-Earth-Orbit (LEO) satellite networks offer a promising avenue for achieving global connectivity, despite certain technical and economic challenges such as high implementation costs and the complexity of network management. Nonetheless, real-time routing remains challenging because of rapid topology changes and strict energy constraints. This paper proposes a GPU-accelerated Eclipse-Aware Routing (EAR) method that simultaneously minimizes hop count and balances energy consumption for real-time routing on an onboard computer (OBC). The approach first employs a Breadth-First Search (BFS)–based K-Shortest Paths (KSP) algorithm to generate candidate routes and then evaluates battery usage to select the most efficient path. In large-scale networks, the computational load of the KSP search increases substantially. Therefore, CUDA-based parallel processing was integrated to enhance performance, resulting in a speedup of approximately 3.081 times over the conventional CPU-based method. The practical applicability of the proposed method is further validated by successfully updating routing tables in a SpaceWire network.
Details
Parallel processing;
Topology;
Solar energy;
Satellite communications;
Shortest-path problems;
Infrastructure;
Graphics processing units;
Rocket launches;
Routing (telecommunications);
Data processing;
Communications networks;
Algorithms;
Energy efficiency;
Airborne/spaceborne computers;
Real time;
Satellite networks;
Low earth orbit satellites;
Data transmission;
Low earth orbits
; Lee, Heoncheol 2
; Han Myonghun 3 1 School of Electronic Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea
2 School of Electronic Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Republic of Korea
3 Agency for Defense Development, Daejeon 34186, Republic of Korea