Adaptive Network Management Service Based on Control Relation Graph for Software-Defined LEO Satellite Networks in 6G

被引:1
|
作者
Chen, Long [1 ]
Tang, Feilong [2 ]
Li, Xu [3 ]
Liu, Jiacheng [4 ]
Zhu, Yanmin [2 ]
Yu, Jiadi [2 ]
机构
[1] Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada
[2] Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China
[3] Huawei Technol Co Ltd, Shenzhen 518129, Peoples R China
[4] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Hong Kong 999077, Peoples R China
基金
中国国家自然科学基金;
关键词
Control relation graph; network management service; software -defined LEO satellite networks; PLACEMENT; ASSIGNMENT;
D O I
10.1109/TSC.2024.3440028
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As the most important incremental component in the advent of the 6G era, Low-Earth-Orbit (LEO) satellite networks are becoming increasingly instrumental, and their integration with Software-Defined Networking (SDN) is progressively recognized as a potent strategy for evolving toward truly service-centric networks, where networks are flexiblely reconstructed based on the service demands. Within such networks, the SDN controllers are responsible for network management by making service-aware resource orchestration. Hence, the placement and assignment of controllers emerge as one of the most critical aspects of the network management service, which becomes particularly challenging when confronted with the unique complexities posed by LEO satellite networks, characterized by their highly dynamic topology and unpredictable load fluctuations. In this paper, for the first time, we tackle the issue of controller placement and assignment with a focus on delivering network management services. Firstly, we formulate the adaptive controller placement and assignment problem. Then, we propose the control relation graph (CRG) to capture the control overhead. Next, we present the CRG-based controller placement and assignment algorithm and the sliding window based traffic prediction method. The lookahead-based improvement algorithm is designed to further decrease management costs. Finally, we conduct a series of theoretical analyses including time complexities. Extensive emulation results demonstrate that our algorithms outperform related schemes in terms of response time and load balancing.
引用
收藏
页码:3122 / 3139
页数:18
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