Dynamic Routing for Integrated Satellite-Terrestrial Networks: A Constrained Multi-Agent Reinforcement Learning Approach

The integrated satellite-terrestrial network (ISTN) system has experienced significant growth, offering seamless communication services in remote areas with limited terrestrial infrastructure. However, designing a routing scheme for ISTN is exceedingly difficult, primarily due to the heightened comp...

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Veröffentlicht in:	IEEE Journal on Selected Areas in Communications Jg. 42; H. 5; S. 1204 - 1218
Hauptverfasser:	Lyu, Yifeng, Hu, Han, Fan, Rongfei, Liu, Zhi, An, Jianping, Mao, Shiwen
Format:	Journal Article
Sprache:	Englisch Japanisch
Veröffentlicht:	New York IEEE 01.05.2024 Institute of Electrical and Electronics Engineers (IEEE) The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Ablation Algorithms Computer Science - Artificial Intelligence Computer Science - Machine Learning Computer Science - Networking and Internet Architecture constrained multi-agent reinforcement learning Constraints Delays dynamic routing algorithm Electrical Engineering and Systems Science - Systems and Control end-to-end delay Energy consumption Ground stations Heuristic algorithms Integrated satellite-terrestrial networks Lagrange multiplier Machine learning Multiagent systems Optimization Packet loss Packet transmission Routing Satellites Topology
ISSN:	0733-8716, 1558-0008
Online-Zugang:	Volltext
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