TY - GEN
T1 - Resource management architecture and technology for coordination of computing and networking in satellite-Terrestrial integrated network
AU - Liu, Xianfeng
AU - Song, Yaqin
AU - Xu, Hui
AU - Xiang, Zihao
AU - Wang, Hucheng
AU - Cheng, Zhimi
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2023
Y1 - 2023
N2 - With the development of computing capability onboard, satellite-Terrestrial integrated network presents characteristics such as large scale, complex topology, and heterogeneous and diverse resources, making it difficult to accurately adapt to the resource requirements of different services. This article analyses the diverse and heterogeneous computing and networking resources in satellite-Terrestrial integrated network, and presents an intelligent resource management and control architecture. This architecture aims to achieve intelligent collaborative management of multi-dimensional and multi-domain computing and networking resources in space and ground, and to provide resources for diverse scenarios as needed. Based on the proposed architecture, a knowledge space-based resource management mechanism is proposed to achieve deep integration of computing, data, algorithms, and networks, and to improve the effectiveness of resource orchestration. Meanwhile, a highly dynamic end-To-end network slicing management mechanism is presented to adapt to the differentiated needs and to provide on-demand network services for users. Finally, the experimental results showed that a dynamic deployment policy for the satellite-Terrestrial integrated network can be generated in just 1.3 seconds using the greedy algorithm to meet the computing and networking resource requirements of the service scenario on a scale of 20 satellites, which verified the rationality and effectiveness of the intelligent resource management architecture.
AB - With the development of computing capability onboard, satellite-Terrestrial integrated network presents characteristics such as large scale, complex topology, and heterogeneous and diverse resources, making it difficult to accurately adapt to the resource requirements of different services. This article analyses the diverse and heterogeneous computing and networking resources in satellite-Terrestrial integrated network, and presents an intelligent resource management and control architecture. This architecture aims to achieve intelligent collaborative management of multi-dimensional and multi-domain computing and networking resources in space and ground, and to provide resources for diverse scenarios as needed. Based on the proposed architecture, a knowledge space-based resource management mechanism is proposed to achieve deep integration of computing, data, algorithms, and networks, and to improve the effectiveness of resource orchestration. Meanwhile, a highly dynamic end-To-end network slicing management mechanism is presented to adapt to the differentiated needs and to provide on-demand network services for users. Finally, the experimental results showed that a dynamic deployment policy for the satellite-Terrestrial integrated network can be generated in just 1.3 seconds using the greedy algorithm to meet the computing and networking resource requirements of the service scenario on a scale of 20 satellites, which verified the rationality and effectiveness of the intelligent resource management architecture.
KW - artificial intelligence
KW - coordination of computing and networking
KW - network slicing
KW - resource management and control
KW - satellite-Terrestrial integrated network
UR - http://www.scopus.com/inward/record.url?scp=85182398175&partnerID=8YFLogxK
U2 - 10.1117/12.3007765
DO - 10.1117/12.3007765
M3 - Conference contribution
AN - SCOPUS:85182398175
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Eighth Asia Pacific Conference on Optics Manufacture and Third International Forum of Young Scientists on Advanced Optical Manufacturing, APCOM and YSAOM 2023
A2 - Zhang, Xuejun
A2 - Wang, Xiaoyong
A2 - Dai, Yifan
A2 - Kong, Lingbao
A2 - Zhang, Dawei
A2 - Gong, Feng
A2 - Li, Lihua
PB - SPIE
T2 - 8th Asia Pacific Conference on Optics Manufacture, APCOM 2023 and 3rd International Forum of Young Scientists on Advanced Optical Manufacturing, YSAOM 2023
Y2 - 4 August 2023 through 6 August 2023
ER -