Priority-Based Load Balancing With Multiagent Deep Reinforcement Learning for Space-Air-Ground Integrated Network Slicing

Space-air-ground integrated network (SAGIN) slicing has been studied for supporting diverse applications, which consists of the terrestrial layer (TL) deployed with base stations (BSs), the aerial layer (AL) deployed with unmanned aerial vehicles (UAVs), as well as the space layer (SL) deployed with...

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Vydané v:	IEEE internet of things journal Ročník 11; číslo 19; s. 30690 - 30703
Hlavní autori:	Tu, Haiyan, Bellavista, Paolo, Zhao, Liqiang, Zheng, Gan, Liang, Kai, Wong, Kai-Kit
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.10.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Autonomous aerial vehicles Delays Load balancing Load balancing (LB) Load management Low earth orbit satellites Low earth orbits multiagent deep deterministic policy gradient (MADDPG) Multiagent systems multiobjective optimization Multiple objective analysis Network slicing radio access network slicing Resource allocation Resource management Satellites Space-air-ground integrated networks space-air–ground integrated networks (SAGINs) Unmanned aerial vehicles
ISSN:	2327-4662, 2327-4662
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