TY - GEN
T1 - Service-Oriented Resource Allocation in SDN Enabled LEO Satellite Networks
AU - He, Jingchao
AU - Cheng, Nan
AU - Yin, Zhisheng
AU - Zhou, Haibo
AU - Xu, Wenchao
AU - Peng, Haixia
AU - Zhou, Conghao
AU - Zhang, Ruqian
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - As an integral component of space-air-ground integrated networks (SAGINs), the low Earth orbit (LEO) satellite networks have displayed immense potential in providing ubiquitous connectivity and broadband mobile communication. However, the intrinsic dynamics of LEO satellites poses unprecedented challenges in network management, multi-dimensional resource scheduling, and service delivery. In this paper, we study the service function chain (SFC) orchestration in dynamic LEO satellite networks, with the aim of achieving flexible and efficient service provision. Considering the service requirements and the load fairness of LEO satellite networks, we formulate the SFC deployment problem as an integer nonlinear programming (INLP) problem. We then introduce a load-aware SFC orchestration algorithm to improve serving capacity and load fairness. Additionally, we address the issue of SFC migration in dynamic LEO satellite networks to ensure service continuity. To minimize the service interruption and network resource wastes, a Tabu search (TS)-based approach is presented to optimize the virtual network function (VNF) migration. Simulation results demonstrate that our proposed approaches outperform the benchmark by a substantial margin in terms of load fairness, without compromising service acceptance.
AB - As an integral component of space-air-ground integrated networks (SAGINs), the low Earth orbit (LEO) satellite networks have displayed immense potential in providing ubiquitous connectivity and broadband mobile communication. However, the intrinsic dynamics of LEO satellites poses unprecedented challenges in network management, multi-dimensional resource scheduling, and service delivery. In this paper, we study the service function chain (SFC) orchestration in dynamic LEO satellite networks, with the aim of achieving flexible and efficient service provision. Considering the service requirements and the load fairness of LEO satellite networks, we formulate the SFC deployment problem as an integer nonlinear programming (INLP) problem. We then introduce a load-aware SFC orchestration algorithm to improve serving capacity and load fairness. Additionally, we address the issue of SFC migration in dynamic LEO satellite networks to ensure service continuity. To minimize the service interruption and network resource wastes, a Tabu search (TS)-based approach is presented to optimize the virtual network function (VNF) migration. Simulation results demonstrate that our proposed approaches outperform the benchmark by a substantial margin in terms of load fairness, without compromising service acceptance.
KW - Low Earth orbit (LEO) satellite network
KW - satellite load
KW - service function chain (SFC)
KW - software-defined networking (SDN)
UR - https://www.scopus.com/pages/publications/85178257775
U2 - 10.1109/PIMRC56721.2023.10293826
DO - 10.1109/PIMRC56721.2023.10293826
M3 - 会议稿件
AN - SCOPUS:85178257775
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
BT - 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2023
Y2 - 5 September 2023 through 8 September 2023
ER -