The increasing complexity of future networks demands intelligent,scalable,and adaptive management solutions.Digital twin network(DTN)provides a high-fidelity replica of the physical network for monitoring and optimiza...The increasing complexity of future networks demands intelligent,scalable,and adaptive management solutions.Digital twin network(DTN)provides a high-fidelity replica of the physical network for monitoring and optimization,but faces significant limitations,including complex modeling,high synchronization overhead,and limited scalability.Foundation models(large pre-trained AI models)offer powerful semantic understanding and reasoning abilities,yet suffer from high training costs,risks of generating hallucinations,and limited interpretability.To address these challenges,this paper proposes an integrated architecture that combines DTN with foundation models,leveraging their complementary strengths.DTN ensures fidelity and domain-specific modeling,and acts as a validation platform to help facilitate the training and verification of network foundation models.Foundation models enable data-driven automation,downstream model generation,and adaptive decision-making.Furthermore,we present use cases related to twin network configuration verification and protocol generation,demonstrating enhanced scalability,efficiency,and intelligence for intelligent networks by bridging foundation models and digital twin.展开更多
A multi-maneuver approach to transition from Lunar Frozen Orbit(LFO)to a cislunar L2 Near Rectilinear Halo Orbit(NRHO)was developed in this research.LFO was utilized to provide the navigation or communication platform...A multi-maneuver approach to transition from Lunar Frozen Orbit(LFO)to a cislunar L2 Near Rectilinear Halo Orbit(NRHO)was developed in this research.LFO was utilized to provide the navigation or communication platform for lunar exploration.They are long-term stable orbits with constant orbital elements on average.Subsets of Halo orbit families,known as NRHO,are orbits that are nearly stable.Due to their important locations in cislunar space,the L2 NRHO are considered as possible launching platforms for deep space or lunar exploration mission.For upcoming cislunar space exploration missions,the low fuel consumption transfer approach between these orbits is very valuable.Utilizing the maximum stretching direction to determine the insertion maneuver,the spacecraft may rapidly approach NRHO.In order to optimize the transfer trajectories,a nonlinear programming problem was developed.The optimization results with different transfer windows in the high-fidelity model were given for the transfer from LFO to NRHO,demonstrating the reliability of the proposed strategy.展开更多
基金supported by National Key R&D Program of China(No.2024YFB2906701).
摘要The increasing complexity of future networks demands intelligent,scalable,and adaptive management solutions.Digital twin network(DTN)provides a high-fidelity replica of the physical network for monitoring and optimization,but faces significant limitations,including complex modeling,high synchronization overhead,and limited scalability.Foundation models(large pre-trained AI models)offer powerful semantic understanding and reasoning abilities,yet suffer from high training costs,risks of generating hallucinations,and limited interpretability.To address these challenges,this paper proposes an integrated architecture that combines DTN with foundation models,leveraging their complementary strengths.DTN ensures fidelity and domain-specific modeling,and acts as a validation platform to help facilitate the training and verification of network foundation models.Foundation models enable data-driven automation,downstream model generation,and adaptive decision-making.Furthermore,we present use cases related to twin network configuration verification and protocol generation,demonstrating enhanced scalability,efficiency,and intelligence for intelligent networks by bridging foundation models and digital twin.
基金Supported by the National Natural Science Foundation of China(12372046)Natural Science Foundation of Jiangsu Province(BK20220130)。
摘要A multi-maneuver approach to transition from Lunar Frozen Orbit(LFO)to a cislunar L2 Near Rectilinear Halo Orbit(NRHO)was developed in this research.LFO was utilized to provide the navigation or communication platform for lunar exploration.They are long-term stable orbits with constant orbital elements on average.Subsets of Halo orbit families,known as NRHO,are orbits that are nearly stable.Due to their important locations in cislunar space,the L2 NRHO are considered as possible launching platforms for deep space or lunar exploration mission.For upcoming cislunar space exploration missions,the low fuel consumption transfer approach between these orbits is very valuable.Utilizing the maximum stretching direction to determine the insertion maneuver,the spacecraft may rapidly approach NRHO.In order to optimize the transfer trajectories,a nonlinear programming problem was developed.The optimization results with different transfer windows in the high-fidelity model were given for the transfer from LFO to NRHO,demonstrating the reliability of the proposed strategy.